sample resume for senior data analyst position

• Senior Data Analyst Resume Example

Resume Examples

• Common Tasks & Responsibilities
• Top Hard & Soft Skills
• Action Verbs & Keywords
• Resume FAQs
• Similar Resumes

Common Responsibilities Listed on Senior Data Analyst Resumes:

• Lead data-driven decision-making through advanced statistical analysis and predictive modeling.
• Collaborate with cross-functional teams to align data strategies with business objectives.
• Develop and maintain automated dashboards using cutting-edge visualization tools.
• Mentor junior analysts, fostering skill development and promoting best practices.
• Implement machine learning algorithms to enhance data processing and insights generation.
• Conduct comprehensive data audits to ensure accuracy and integrity of datasets.
• Drive strategic initiatives by translating complex data into actionable business insights.
• Stay updated with emerging data technologies and integrate them into existing workflows.
• Facilitate remote collaboration using agile methodologies to streamline project delivery.
• Design and optimize ETL processes for efficient data extraction and transformation.
• Engage in continuous learning to adapt to evolving industry trends and technologies.

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Senior Data Analyst Resume Example:

• Spearheaded the implementation of a company-wide AI-driven predictive analytics platform, resulting in a 35% increase in forecast accuracy and $12M in cost savings across departments.
• Led a cross-functional team of 15 data scientists and engineers in developing a real-time customer segmentation model, boosting targeted marketing campaign effectiveness by 28% and increasing ROI by 40%.
• Pioneered the adoption of quantum computing techniques for complex data analysis, reducing processing time for large-scale simulations by 75% and enabling more sophisticated risk modeling for the finance department.
• Orchestrated the migration of legacy data systems to a cloud-based data lake architecture, improving data accessibility by 200% and reducing annual infrastructure costs by $1.5M.
• Developed and implemented an automated anomaly detection system using machine learning algorithms, identifying fraudulent transactions with 99.7% accuracy and preventing $8M in potential losses.
• Mentored a team of 8 junior analysts, creating a comprehensive training program that increased team productivity by 40% and reduced onboarding time from 3 months to 6 weeks.
• Designed and executed A/B tests for e-commerce platform optimizations, resulting in a 15% increase in conversion rates and $5M additional annual revenue.
• Collaborated with marketing teams to develop a customer lifetime value model, enabling personalized retention strategies that reduced churn by 22% and increased customer satisfaction scores by 18 points.
• Implemented natural language processing techniques to analyze customer feedback, automating the categorization of 10,000+ weekly comments and reducing manual review time by 80%.
• Data Science
• Data Visualization
• Data Mining
• Machine Learning
• Predictive Modeling
• Data Warehousing
• Data Architecture
• Data Governance
• Data Analysis
• Statistical Analysis
• Data Quality Assurance
• Pricing Strategies
• A/B Testing
• Data Lake Architecture
• Data Security
• Business Intelligence
• R Programming
• Cloud Computing
• Computer Science

Top Skills & Keywords for Senior Data Analyst Resumes:

Hard skills.

• SQL and Database Management
• Data Warehousing and ETL
• Data Modeling and Analysis
• Data Visualization and Reporting
• Statistical Analysis and Modeling
• Machine Learning and Predictive Analytics
• Data Mining and Data Cleaning
• Business Intelligence Tools (e.g. Tableau, Power BI)
• Programming Languages (e.g. Python, R)
• Data Governance and Security
• Data Quality Assurance and Control
• Data Architecture and Design

Soft Skills

• Communication and Presentation Skills
• Collaboration and Cross-Functional Coordination
• Problem Solving and Critical Thinking
• Adaptability and Flexibility
• Time Management and Prioritization
• Attention to Detail and Accuracy
• Data Visualization and Storytelling
• Business Acumen and Industry Knowledge
• Project Management and Planning
• Continuous Learning and Improvement
• Teamwork and Relationship Building

Resume Action Verbs for Senior Data Analysts:

• Interpreted
• Synthesized
• Implemented
• Communicated
• Prioritized

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Resume FAQs for Senior Data Analysts:

How long should i make my senior data analyst resume, what is the best way to format my senior data analyst resume, what certifications should i include on my senior data analyst resume, what are the most common mistakes to avoid on a senior data analyst resume, compare your senior data analyst resume to a job description:.

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• Improve your keyword usage to align your experience and skills with the position
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Related Resumes for Senior Data Analysts:

Senior data engineer, senior data scientist, experienced data analyst, junior data analyst, business data analyst, sql data analyst, big data analyst, data reporting analyst.

Senior Data Analyst Resume Examples

By Silvia Angeloro

Jul 18, 2024

12 min read

Craft your senior data analyst resume: Get the job you’re calculated for. Optimize your skills, qualifications, and experience in a clear and concise manner. Make sure you add data-driven accomplishments to stand out.

Rated by 348 people

• • Led a team that improved intelligence production processes, reducing analysis time by 20% and enhancing decision-making accuracy.
• • Developed rapid, classified responses to strategic inquiries, increasing response efficiency by 30%.
• • Conducted and managed complex research on various intelligence issues, identifying significant factors and developing evidence-backed solutions.
• • Utilized top secret intelligence databases for deep-dive research to support national security initiatives.
• • Created visualization tools and reports based on program statistics to convey key insights to stakeholders.
• • Coordinated with multiple agency departments to ensure intelligence products met operational needs.
• • Provided technical and analytical support, increasing the effectiveness of intelligence data integration by 25%.
• • Leveraged classified and law enforcement data systems to improve responsiveness in intelligence operations.
• • Organized and analyzed complex datasets, resulting in the identification of key security trends.
• • Developed standard operating procedures for the dissemination of intelligence products.
• • Designed and implemented visual and written reports to enhance strategic decision-making.
• • Conducted comprehensive research on emerging intelligence issues and developed action plans.
• • Improved intelligence data sharing practices across multiple platforms, resulting in a 15% increase in collaborative efforts.
• • Created detailed analytical reports to assist operational and strategic intelligence decisions.
• • Implemented process improvements for intelligence data collection and analysis, resulting in streamlined operations.
• • Conducted analytical assessments using unclassified and secret databases to provide actionable intelligence insights.
• • Collaborated with cross-functional teams to integrate diverse data sources into comprehensive reports.
• • Participated in process optimization projects, enhancing data quality and operational efficiency.
• • Developed presentation materials to communicate analytical findings to senior management.

In this article

Writing Your Resume

Must-Have Info

Resume Format

Resume Experience Tips

Resume Summary

Listing Your Skills

Education on Resume

Resume Certifications

Extra Sections

Cover Letter Example

Crafting the perfect senior data analyst resume can be a real "data headache". You have extensive experience, but translating that into a polished resume can be tricky. This guide will help you tackle common challenges like highlighting your achievements without overloading on jargon. Many senior data analysts find it hard to pinpoint which skills to emphasize and how to demonstrate their advanced problem-solving abilities. Moreover, aligning your resume with what hiring managers are looking for can be daunting. Fear not, this guide will break it down step-by-step, offering practical tips to make your resume stand out in a competitive job market.

Selecting the right resume template is crucial for showcasing your expertise effectively. Your resume should not only look professional but also be optimized to capture the attention of hiring managers quickly. It's essential to use a structure that highlights your accomplishments and lends clarity to your complex role.

With over 700 resume examples, find inspiration and create a resume that sets you apart.

Key Takeaways

• Highlighting your achievements and technical proficiency is crucial for a senior data analyst resume, with clear examples of past projects.
• Choosing the right template and format, such as reverse chronological, modern fonts, and saving as a PDF, ensures your resume looks professional and is easy to read.
• Including essential sections like Contact Information, Professional Summary, Key Skills, Professional Experience, Education, and Certifications makes your resume comprehensive and tailored to ATS requirements.
• Craft your experience section to showcase your achievements with specific metrics and action verbs, focusing on outcomes rather than routine tasks.
• Feature both hard and soft skills prominently to catch the attention of hiring managers and ATS, with a focus on data-centric and interpersonal abilities.

What to focus on when writing your senior data analyst resume

A senior data analyst resume should clearly show your advanced skills and extensive experience. It should highlight your ability to analyze large datasets, draw meaningful insights, and make data-driven decisions that drive business success. Include clear examples of past projects, showcasing your technical proficiency and problem-solving prowess.

Boost the impact of your resume with:

• Demonstrated achievements, such as successful data-driven projects.
• Proficiency in tools like SQL, Python, and Excel.
• Strong analytical and critical thinking skills.
• Experience mentoring junior analysts or leading a team.

Must have information on your senior data analyst resume

To craft an effective senior data analyst resume, you need to include essential sections that highlight your expertise and experience. Consider these must-have sections:

• Header with Contact Information
• Professional Summary
• Professional Experience
• Certifications

Additional sections such as Projects, Technical Proficiencies, and Awards can also help strengthen your resume and set you apart. Tailoring these sections to your field will make your application stand out to hiring managers and applicant tracking systems (ATS).

Which resume format to choose

For a senior data analyst resume, the reverse chronological format is ideal because it highlights your extensive experience and career progression. Use modern fonts like Rubik and Montserrat, which look fresh compared to the outdated Arial or Times New Roman. Always save and send your resume as a PDF to ensure the formatting stays consistent. Keep your margins at around 1 inch on all sides, giving your content enough white space to breathe. Use clear section headings to aid ATS in easily parsing your resume, increasing your chances of passing initial screenings.

Your resume should include the following sections: Contact Information, Professional Summary, Skills, Work Experience, Education, Certifications, and Achievements. Use bullet points under each section to make it easy to read.

Resume Mentor's free resume builder handles all of these formatting details for you efficiently.

How to write a quantifiable resume experience section

Crafting the experience section of a senior data analyst resume involves more than just listing your past jobs—it's about showcasing your achievements with clarity. First, order your experiences starting with the most recent. It's recommended to go back about 10-15 years, including relevant job titles. This keeps your resume focused and concise. Tailor each job entry to the specific role you're applying for, ensuring you highlight key skills and accomplishments relevant to that position.

When writing about your experience, use action words or verbs like "analyzed," "designed," and "led" to make your points clear and dynamic. Focus less on routine tasks and more on outcomes and numbers. Metrics like "increased efficiency by 20%" or "reduced costs by $50,000" are impactful.

Now, let's see why the quality of writing matters so much through two contrasting examples.

• • Worked on various projects
• • Did data analysis tasks
• • Coordinated with the team

This example is not effective because it is vague and lacks specifics. It does not highlight any significant achievements or measurable results. The bullets are too generic and do not showcase your skills or how you benefited the company.

• • Increased data processing efficiency by 30% through optimized algorithms
• • Reduced company operating costs by $200,000 annually by refining data workflows
• • Led a team of 5 analysts in a successful company-wide data migration project

In this scenario, specific achievements are laid out with clear metrics. This helps show the direct impact you had on the company. Words like "increased," "reduced," and "led" at the start of each bullet catch the reader's attention. They also help in making it evident how you can add value to potential employers.

When writing your resume, aim to be precise and results-oriented. This helps convey your value quickly to hiring managers, making your experience section stand out in a crowded job market.

Senior data analyst resume experience examples

Looking to amp up your resume game? Don't just skim the data—dive into it! Below you'll find resume experience sections tailored to highlight everything from achievements to tech-savvy skills. Let's transform your resume into a data-driven masterpiece!

Achievement-focused

Highlighting your achievements can make you stand out like a prime number in a sea of integers. Here's how you can do it effectively:

Senior Data Analyst

Tech Solutions Inc.

June 2018 - May 2022

• Increased data processing efficiency by 30% through the implementation of advanced algorithms.
• Led a team that reduced operational costs by $1.5 million annually.
• Awarded Employee of the Year for exceptional contributions to key projects.

Skills-focused

Showcasing your skills can help fill the gaps in any potential employer’s team. Focus on your strongest data-related abilities.

Data Analyst

DataCorp LLC

April 2015 - March 2019

• Proficient in SQL, Python, and R for data manipulation and analysis.
• Advanced Excel skills, including pivot tables and complex formulas.
• Experience with data visualization tools like Tableau and Power BI.

Responsibility-focused

Detailing your responsibilities helps potential employers understand your day-to-day tasks and their impact.

BizData Solutions

January 2016 - December 2021

• Managed a team of junior analysts and interns, providing guidance and mentorship.
• Oversaw the development and maintenance of data systems and databases.
• Coordinated with various departments to gather data requirements and ensure data integrity.

Project-focused

Detail specific projects to underscore your hands-on experience and contributions to the team.

Lead Data Analyst

CloudAnalytics Inc.

March 2017 - Current

• Led a project on customer segmentation that increased marketing effectiveness by 25%.
• Developed a sales forecasting model that improved accuracy by 40%.
• Spearheaded the migration of legacy data systems to Cloud-based solutions.

Result-focused

Focusing on the results of your work can demonstrate the tangible impact you've had.

May 2019 - Present

• Boosted customer retention rates by 15% through detailed analysis of customer feedback.
• Reduced data processing time by 50% via optimization of existing workflows.
• Increased revenue by $2 million through targeted data-driven marketing campaigns.

Industry-Specific Focus

Showcase your experience in a particular industry to appeal to employers looking for niche expertise.

HealthTech Solutions

July 2014 - August 2018

• Gathered and analyzed healthcare data to improve patient care and hospital efficiency.
• Developed prediction models for patient readmission rates, reducing instances by 20%.
• Collaborated with medical staff to ensure accurate data interpretation and application.

Problem-Solving focused

Highlighting your problem-solving abilities can set you apart as a go-to person for complicated issues.

OptiData Systems

February 2016 - November 2020

• Resolved data discrepancies, resulting in a 10% increase in data integrity.
• Implemented a new data quality framework that improved accuracy by 35%.
• Developed solutions to address data processing bottlenecks, reducing processing time by 25%.

Innovation-focused

Emphasize your innovative contributions to demonstrate your forward-thinking nature.

InnovateAnalytics Corp.

August 2017 - Present

• Pioneered the use of machine learning models to predict customer churn.
• Introduced AI-driven analytics tools, saving 500 work hours annually.
• Designed and implemented a new data warehouse system, enhancing data accessibility.

Leadership-focused

Your leadership skills can show employers that you're ready to take on more responsibilities.

Data Analytics Manager

Global Data Solutions

September 2016 - April 2021

• Led a team of 10 analysts, improving team productivity by 20%.
• Developed training programs for new hires, accelerating their onboarding process.
• Conducted performance reviews and provided mentorship to junior team members.

Customer-focused

Show how your work improved customer experience and satisfaction, crucial for many roles.

CustomerFirst Analytics

June 2015 - December 2019

• Analyzed customer feedback to improve product offerings, leading to a 15% increase in customer satisfaction.
• Conducted surveys and focus groups to gather actionable customer insights.
• Collaborated with the customer service team to resolve issues more swiftly.

Growth-focused

Highlight your contributions to the growth and expansion of the company.

Data Analyst Lead

GrowthSphere Inc.

October 2017 - Present

• Developed data-driven strategies that resulted in a 30% growth in annual revenue.
• Identified new market opportunities through rigorous data analysis.
• Worked with the business development team to drive strategic initiatives.

Efficiency-focused

Showcase your ability to make processes more efficient, which is always a valuable skill.

EffiAnalytics

January 2016 - July 2020

• Optimized reporting processes, reducing time spent on report generation by 40%.
• Implemented automated data cleaning processes, saving 10 hours per week.
• Streamlined data collection workflows, resulting in a 25% increase in efficiency.

Technology-focused

Highlighting your familiarity with various technologies can make you more attractive to tech-savvy employers.

TechnoData Inc.

April 2018 - Current

• Utilized Hadoop and Spark for large-scale data processing projects.
• Developed interactive dashboards using Tableau and Power BI.
• Integrated new data analytics software that improved insights and reporting.

Collaboration-focused

Being able to work well with others is just as important as your individual skills.

CollabAnalytics LLC

May 2017 - November 2021

• Collaborated with the marketing and sales teams to implement data-driven strategies.
• Facilitated cross-departmental workshops to improve data literacy.
• Worked closely with IT to enhance data security and integrity.

Training and Development focused

Showcase your ability to train and develop others, a valuable asset for any senior role.

EduData Systems

February 2015 - October 2020

• Developed and conducted training programs for new data analysts.
• Provided ongoing mentorship, increasing junior staff productivity by 20%.
• Designed e-learning modules to enhance team skills in data analysis tools.

Write your senior data analyst resume summary section

Crafting a resume summary for a senior data analyst position is crucial. This section quickly tells potential employers about your skills and experiences. It should be concise yet compelling. Aim to highlight your expertise and how you add value. Always use simple words, and make every sentence count.

The first example is poorly written. It lacks specifics, overuses generic terms, and doesn't highlight any unique achievements or skills. It fails to grab your attention because it doesn’t show how the candidate stands out. It also doesn’t use action verbs or metrics to quantify accomplishments.

The second example is excellent. It highlights years of experience and specific skills. It uses metrics to show impact, making it more credible. The candidate presents a clear value proposition. This summary is clear, precise, and compelling.

The difference between a summary, resume objective, resume profile, and summary of qualifications lies in their focus and format. A summary provides an overview of experience and skills. A resume objective states your career goals. A resume profile is similar to a summary but often shorter. A summary of qualifications lists key achievements and skills in bullet points. Each serves a different purpose; choose the one that fits you best.

Listing your senior data analyst skills on your resume

In your senior data analyst resume, the skills section is crucial. It can be a standalone section or integrated into other parts like experience and summary. Skills separate your expertise and strengths from the rest of your resume, ensuring that hiring managers notice them.

Strengths and soft skills include abilities like communication and problem-solving. Hard skills refer to specific technical abilities you gain through training or experience, such as proficiency in data analysis software.

Skills and strengths can serve as keywords in your resume. These keywords help your resume stand out to both humans and applicant tracking systems (ATS). Keywords that reflect your skills and strengths improve your chances of being noticed.

This example is effective because it lists relevant skills specific to a senior data analyst role. The skills are clear and concise, making it easy for employers to see your expertise. Using keywords makes it likely that hiring managers and ATS will notice your resume.

Best hard skills to feature on your senior data analyst resume

For a senior data analyst, hard skills should show expertise in data analysis and the ability to derive actionable insights. These skills demonstrate not only proficiency but also your ability to handle complex data-related tasks.

Hard Skills

• Data Mining
• Statistical Analysis
• Machine Learning
• Data Visualization
• Big Data Technologies
• R Programming
• ETL Processes
• Predictive Modeling
• Data Warehousing
• Data Cleaning
• A/B Testing

Best soft skills to feature on your senior data analyst resume

Soft skills for a senior data analyst should highlight interpersonal abilities and problem-solving skills. These skills show that you can communicate your findings effectively and work well in a team.

Soft Skills

• Communication
• Problem-Solving
• Critical Thinking
• Time Management
• Attention to Detail
• Adaptability
• Analytical Thinking
• Decision-Making
• Collaboration
• Conflict Resolution
• Project Management

How to include your education on your resume

The education section is an important part of your senior data analyst resume. It should highlight your relevant academic background and credentials. Tailor this section to the job you're applying for, ensuring that only pertinent education is included. If you have a high GPA or graduated with honors like cum laude, you should note this as it emphasizes your academic excellence. Clearly list your degree, the institution, and the dates attended.

This example is poorly written. It includes irrelevant education details such as a high school diploma and a degree in history, which do not relate to a senior data analyst position. It lacks details like GPA or honors, missing opportunities to impress.

This example is well-written. The degrees listed are directly relevant to a senior data analyst role. It highlights impressive GPAs and mentions graduating cum laude. This effectively showcases relevant academic achievements and aligns the education background with the job applied for.

How to include senior data analyst certificates on your resume

Including a certificates section in your senior data analyst resume is crucial. List the name of each certification prominently. Include the date you achieved the certification to show how recent it is. Add the issuing organization to establish the credential's credibility. Certificates can also be featured in the header. For example:

Here’s why this example works well. It lists recognized certifications like CDMP and Google Data Analytics Professional Certificate. These are highly relevant to a senior data analyst role. The inclusion of the issuing organizations, DAMA International and Google, strengthens the credibility. These details demonstrate your commitment to professional growth.

Extra sections to include in your senior data analyst resume

Creating a well-rounded resume for a senior data analyst can be the key to standing out in a competitive job market. Including sections such as language skills, hobbies, volunteer work, and books can give a more comprehensive view of your qualifications and personality.

Language section — Highlight your proficiency in multiple languages to show your ability to communicate with diverse teams and clients. This can also open doors to international projects.

Hobbies and interests section — List activities that show analytical thinking, like chess or programming, to demonstrate your passion for problem-solving outside of work. This can make you more relatable and interesting to potential employers.

Volunteer work section — Detail your involvement in community service or non-profits to exhibit your willingness to apply your skills for social good. This indicates strong ethical values and leadership qualities.

Books section — Mention books related to data analytics or personal growth that you have read to showcase your continuous learning and passion for the field. This can position you as a proactive and knowledgeable professional.

Each of these sections adds depth to your resume, making you a more compelling candidate. They offer recruiters and hiring managers a glimpse into the unique skills and qualities you bring to a senior data analyst role.

Pair your senior data analyst resume with a cover letter

A cover letter is a document sent with your resume to provide additional information on your skills and experience. It’s your chance to explain why you are a good fit for the job and show your enthusiasm for the role.

A cover letter can help you stand out by giving you an opportunity to highlight your achievements and demonstrate your communication skills. It allows you to provide context to your resume and show the employer how your background aligns with their needs.

For a senior data analyst, the cover letter should focus on your expertise in data analysis, proficiency with software and tools, and experience in driving data-driven strategies. Mention specific projects where you delivered significant insights or helped improve business outcomes. Highlight your ability to work with cross-functional teams and your knack for problem-solving.

Create your impactful cover letter with ease using Resume Mentor's cover letter builder. Its simple interface ensures a stress-free experience, and exporting your cover letter as a PDF helps protect your content and formatting. Start crafting your perfect cover letter today!

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Senior Data Analyst Resume Samples

The guide to resume tailoring.

Guide the recruiter to the conclusion that you are the best candidate for the senior data analyst job. It’s actually very simple. Tailor your resume by picking relevant responsibilities from the examples below and then add your accomplishments. This way, you can position yourself in the best way to get hired.

Craft your perfect resume by picking job responsibilities written by professional recruiters

Pick from the thousands of curated job responsibilities used by the leading companies, tailor your resume & cover letter with wording that best fits for each job you apply.

Create a Resume in Minutes with Professional Resume Templates

• Develop and maintain positive and professional working relationships with all levels of management, external customers and vendors
• Work directly with advisory Managing Directors and Principals to develop ideas or client requests into working solutions
• Works with the management team and contribute to the development and implementation of department strategies
• Makes recommendations about methods to collect, analyze and manage data to improve data quality and the efficiency of data systems
• Develop reporting and analysis to measure the effectiveness of direct marketing channels; make data driven recommendations that optimize channel performance
• Assist in development of reports, providing content and writing of key observations
• Prioritize analyses, develop tactical approaches, and manage analyst work streams
• With admin support, manage internal Shared Drive; develop an enhanced workpaper naming convention for SharePoint site; and manage access to workpapers
• Works with, and reviews the work product of, analytics development resources to develop high quality, efficient solution components
• Manage and develop relations with Dentsu Aegis Network team and our third-party attribution provider
• Assist in the development and preparation of ad hoc reports on specific issues to help practice managers and physicians make decisions
• Assist with the development of a measurement and learning plan including establishing campaign performance benchmarks, goals, and projections
• Work with Product/Program Manager(s) to manage the product development process and report progress toward achieving
• Create, extract and perform complex reports utilizing various databases and providing recommendations to different levels of management
• Strong problem solving skills, self-motivation and the capacity to work under pressure with tight deadlines and strong attention to detail
• Self motivated and proactive, with attention to detail, deadlines, and good quality control practices
• Be proficient in SQL and a visualization tool (Tableau or Spotfire); a working knowledge of data manipulation in SAS is
• Strong knowledge of SQL and Business Intelligence Tools (Tableau, Qlik, BusinessObjects, etc.)
• Knowledge of HSD tables and Quest analytics highly desired
• Strong knowledge of Tableau
• Strong attention to detail, testing to identify defects, and ability to drive remediation
• Should be proficient in Business Analysis, Business Knowledge, Software Engineering Leadership, Architecture Knowledge and Technical Solution Design
• Ability to work well under deadlines, ability to work in a multi-tasking production environment to make good judgments about competing priorities
• Strong knowledge of working on databases, BI tools like BO, Cognos, Microstartegy and visual tools like Tableau

15 Senior Data Analyst resume templates

Read our complete resume writing guides

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• Provide accurate data analysis and reporting for business decision-making
• Develop and implement new analytics and reporting driven by business needs
• Serve as internal consultant providing accurate and timely analytics and reporting
• Lead internal projects focused on revenue/profit enhancement opportunities – direct SQL database inquiries involving very large data sets, develop hypotheses and analyses in excel, present results to internal clients and executives
• Develop new statistical predictive models to forecast demand, including pricing models
• Communicate and explain demand models (inputs, outputs, rationale, gaps) and recommendations to senior management
• Partner with cross-functional teams to ensure that inventory flows and product assortments support performance goals and forecast demand
• Make recommendations based on forecasted demand scenarios
• Use data analysis to validate business and model assumptions
• Conduct data mining and analysis to uncover trends and correlations to better predict demand
• Provide full reference data support which includes security setups, trade flow, problem resolution, and synchroncization across systems for one or more of the following application groups
• BPS/SMR (BPS 006 and 069, RBC BackOffice/SMR, Bloomberg, Anvil, BATS, GLOSS)
• ICI/BPS (ICI Impact, BPS 006, FIFE, BondDesk, WinFITS/MBSE, Showcase)
• NY SecMas/Sophis (NY Security Master, Sophis, Reuters)
• Interpret vendor-provided data (IDC, Bloomberg) as well as all manner of official documentation related to security issuance and subsequent actions ( including term sheets, official statements (OS), escrow agreements, filings, call notices, and DTCC notifications) and relate to specific security descriptive data points to issue accuracy and completeness of security reference data. Escalate discrepancies to data vendors and follow issues through to resolution
• Execute scheduled update and maintenance processes for security data, security pricing, and compliance; for example: preparing pricing uploads by extracting and evaluating prices from multiple sources, reviewing customer confirmation for complete security disclosures, and creating reports for business partners using multiple data sources
• Develop specific areas of expertise within security reference data; for example: foreign securities, yield calculations, industry ratings, confirms/statements, or asset classification
• Within your area of expertise, assume a leadership role supporting these activities
• Problem escation and resultions
• Identification of system issues
• Documentation of both general information and specific procedures for use by the entire department
• Preparation of requirements for system fixes and enhancements both for internal IT and vendor systems
• Testing and test documentation for system fixes and enhancements
• Establish new department procedures as needed to support new requests for data or to ensure accuracy; prepare process documentation for department use and audit requirements
• Support WM and CM projects as a subject matter expert for Security Reference Data
• Support WM CAS conversions through review of securities coming in for new situations/security types, identification of securities not pre-existing on our systems; setup global securities as well as privately-held or restricted securities; and coordination with the conversion team
• Develop working knowledge of query and macro tools. Be able to modify existing queries or tools to meet new requests/requirements
• Participate the internal and external audits as required
• Resolve discrepancies and errors in a timely manner, particularly as related to pending trades
• Appropriately prioritize and complete a variety of requests, issues, tasks, and projects ranging in duration from intraday to a year or more
• Escalate issues promptly to mangement as required
• At least three years experience working with across instrument types in an operational capacity at a brokerage firm
• Series 99, Series 7 or equivalent preferred
• A minimum education level of: Bachelor of Arts/Sciences Degree (4-year)
• Experience in music, entertainment, and/or television industry a plus, but not required
• Familiar with statistical packages (e.g., SPSS, SAS, etc.)
• Familiar with database (e.g., SQL Server, MS Access, MySQL) and ability to write simple SQL statements
• Develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality
• Contribute a business or process perspective during design reviews
• Assess solutions in concert with the design team, identify and escalate issues and mitigation plans to business and technology leadership
• Conduct research to determine if solutions to business requirements currently exist within or outside the technology unit, and if not, whether new solutions are feasible
• Analyze impact of proposed solution across the business, cross impacted partners in business, operations and technology across LOBs
• Assist Quality Assurance teams to ensure that requirements documentation can be easily translated into test plans and test cases
• Facilitate implementation of new functionality through training sessions, demos, and the development of appropriate documentation
• 5-7 years of experience with data and business analysis, including problem solving
• Strong knowledge of and experience with reporting packages (Business Objects etc), databases (SQL etc), programming (XML, Javascript, or ETL frameworks)
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy with ability to ‘tell the story&#8217
• Excellent written and oral communication skills and demonstrated strong ability to interact/influence with both business and technology partners
• Proficiency in Python, PERL, Shell Scripting and macros
• Provide rapid development services for critical reporting and process improvement projects
• Support with the creation of, maintenance of, and integrate of metrics related to into a common reporting and analytics solution
• Assist with the definition of metrics and measurements to provide governance to processes
• Perform ad-hoc reporting and analysis
• Assist with the development of and performance of predictive analytics and the transformation of data to business intelligence
• Support with the execution of project plans
• Support and act as a leader with end to end process of data sourcing, importing, cleaning, transforming, validating and modeling into a meaningful purpose such as illustrative charts, graphs, tables, dashboards, etc
• Be creative and resourceful to solve problems to analyze and interpret the data, which will require exceptional pattern recognition and data interrogation techniques
• Have a solid understanding of how databases work, and querying and coding languages to retrieve and manipulate the data for desired affect
• Work closely with project and process teams to design procedures that will support data mining and business analysis
• Power User (five or more years of experience) with Business Intelligence tools such as OBIEE and Tableau, and working knowledge of big data tools such as Datameer, Hadoop, Teradata and Aster
• Working knowledge of SQL query writing, coding/programming and leveraging procedural languages
• Experience in metrics, reporting, dashboards, scorecards and analytics
• Knowledge of financial services products, financial crimes experience preferred
• Bachelor’s degree in a technical discipline such as Computer Science, Information Systems, Mathematics, Statistics, Engineering, Physics, etc
• Extremely strong analytical skills, including pattern recognition
• Willingness to learn and develop expertise in areas outside of core comfort zone
• Support key Personalization initiatives and processes to develop and optimize statistical approaches that model customer multi-channel purchase behavior with respect to seasonality, promotion, brand, and/or product in a retail environment
• Analyze, interpret, and summarize findings that serve to optimize and continuously improve Personalization processes, algorithms, and performance objectives
• Recommend and implement best practices, provide actionable insights, and identify business opportunities in a collaborative team environment
• Apply knowledge of experimental designs to implement and analyze results from extensive Personalization tests in both online and in-store contexts (including recommendation engine results) using standard statistical tests
• Bachelor's degree (advanced degree preferred) in statistics/applied statistics, machine learning, mathematics, econometrics, computer science, or other quantitative discipline
• 3+ years experience with SQL assembling large data sets from both structured and unstructured sources using data marts/warehouses such as Oracle and Teradata
• Proven ability to implement automated, scalable, efficient, and reliable processes/programs to derive, transform, model, and score large data sets
• Experienced formulating, implementing, and validating predictive models using linear/logistic regression, decision trees, boosted trees, and/or neural networks
• Knowledgeable implementing clustering solutions and applying dimensionality reduction techniques such as factor analysis, principal components analysis, and/or SVD
• Must be proficient with one or more statistical software packages such as SAS, R, or SPSS (SAS and SAS Macro development strongly preferred)
• Ability to communicate and shape complex analytical information into actionable business recommendations
• Proficiency in Microsoft Office software (Excel, PowerPoint, Word)
• Ability to manage concurrent projects at different stages of completion
• Perform tasks with a high degree of accuracy and attention to detail
• Demonstrate excellent oral and written communication skills
• Ability to be flexible and deal with changing priorities and timelines/due dates
• Data mining and analysis of both structured and unstructured data, especially clickstream data
• Ability to answer marketing/merchandising questions with analytical reports on consumer behavior
• 3+ years of quantitative and analytical experience supporting marketing or merchandising in a multi-channel retail environment
• Design and evaluate statistical experiments to test customer behavior
• Degree in Engineering / Computing / Actuarial Science / Statistics
• Demonstrated ability to work independently yet interact effectively with different levels of management
• Corporate work ethics – integrity being paramount importance
• Serve as a subject matter expert on various projects as appropriate
• Serve as a Business Analyst working with all business lines, gathering and documenting project and business requirements, with a specific focus on data requirements
• Extensive data management experience
• Operational and management experience with Eagle PACE platforms preferred
• Mid-level technology skills (systems implementation, data manipulation, data feed support)
• Responsible for both leading and participating in a team of analysts focused on the analysis, design, implementation, and follow up of the migration of data from disparate applications to go-forward applications in the Hanesbrands Supply Chain applications portfolio
• Develop an in-depth understanding of the data requirements of go-forward applications
• Participate in developing the methods for documenting data templates for various types of data
• Document data templates for scenarios supported by go-forward applications
• Lead a team of analysts in evaluating target application sets in consolidation and acquisition projects and mapping data requirements to the documented data templates, identifying data gaps and working with applications teams on solutions to address those gaps
• Demonstrate an effective and consistent use of technology in the performance of job responsibilities
• Reviews and ensures that major data architectural designs are consistent, maintainable, flexible, and cost effective for Hanesbrands. Utilize the data architecture review process to introduce changes to the Hanesbrands roadmaps and standards based on project requirements to ensure that it stays up-to-date and continues to evolve. Articulates the tradeoffs, benefits and risks of all data and design solutions
• Provides analysis to support development of vision, data strategy, data architecture and the overall design and development of HBI Supply Chain systems as needed. Provides consultation to application owners, business partners and peer groups regarding long and short-range data solutions that meet business requirements
• Diagnoses data problems effectively and determine solution options with consideration to business impact
• Adhere to enterprise architecture strategies, principals, standards, policies and procedures. Understands and ensures compliance with IT strategy
• Understand industry trends, emerging technologies and standards in order to evolve the Hanesbrands Standards and Roadmap
• Bachelor’s degree or equivalent work experience defined as 7 or more years of overall experience with data analysis for major software systems
• Excellent knowledge of data requirements for a consumer packaged goods type of company that performs vertical manufacturing
• Ability to quickly assess the impact of data changes on the business, application relationships and information flow
• Ability to function as a thought leader for the Supply Chain strategy and vision
• Strong ability to facilitate collaboration among senior technical team members and senior business leaders
• In-depth knowledge of design considerations for high volume transaction systems
• In-depth knowledge of design considerations for large database implementations
• Experience defining and implementing information and data architecture governance, including acting as a design authority for information and data within projects and programs
• Ability to lead, motivate and participate in cross functional teams, providing mentoring and support to junior team members
• Excellent interpersonal and communications skills - lead, collaborate, facilitate, and negotiate as necessary
• Ability to define and manage the scope of data tasks and execute projects on time and within budget, escalating exceptions in a timely manner
• Excellent research skills, ability to leverage available tools such as subscription services, trade press, Internet or other online services
• A wide base of experience in many disciplines of information technology
• Strong consensus building skills
• Effective use of data analysis tools (SQL, Excel, etc.) to access and manipulate data across a range of database and information platforms
• Must be a self-starter with the skills required to be able to motivate and influence across all levels of the organization
• Ability to work flexible hours during key implementation activities
• Ability to travel both domestically and internationally to perform data analysis functions
• Work with key stakeholders and other members of the Digital Insights team to define and manage online customer insights through definition of KPIs, web metrics capabilities and reporting
• Support Digital Channel initiatives for TD’s Credit Card and Insurance teams through data gathering, analysis, business cases and providing monthly trended forecast and plan information
• Analyze trends in both internal and vendor-supplied data to interpret customer relationships and make appropriate recommendations to key stakeholders within the organization
• Contribute to presentations for senior management that clearly and concisely present findings and recommendations
• Work with other members of the Data Analytics team to define and establish standards, processes and policies for an online datamart
• Participate in the education of business partners in the area of data analytics
• Stay abreast of industry trends and innovations and drive new analytics initiatives that contribute to business goals
• Will be naturally inclined to take the initiative on projects
• Will have an entrepreneurial drive that will allow you to create/complete what does not currently exist
• Have a Web Strategy background that will inform your advocacy and selling skills – you must be persuasive and collaborative
• Will be patient yet able to manage rapidly escalating pace of change within the bank
• Review business requirements with project teams to propose and produce technical documentation such as data architecture, data modeling, data dictionary, source to target mapping with transformation rules, ETL data flow design, and test cases
• Discover, explore, analyze and document data from all source and target systems to better understand the total scope of Data Availability at JPMC
• Participate in the Agile development process to develop automated data pipes
• Optimize queries, data aggregations, and data pipes and improve data models in order to optimize and improve data delivery performance
• Collaborate with other data engineers to provide development coverage, support, and knowledge sharing and mentoring of junior team members
• 8+ years total professional experience in software development
• 5+ years of experience creating/maintaining complex SQL against dimensional data models
• Moderate hands-on KornShell scripting experience
• Proven critical thinking ability, with superior verbal and written communication skills
• Proven ability to work independently and take on ownership of complex processes in a very dynamic and adaptive environment
• Interest in Consumer Banking innovations and enhancing customer experiences
• Experience with Hadoop, Greenplum and other “Big Data” solutions
• Experience in Teradata and Teradata SQL Assistant software
• Develop and design reports, financial schedules, dashboards, and analyses using a variety of data-mining and presentation tools
• Extract data from multiple sources and deliver in a unified format
• Drive efficiencies within the current reporting structure including enhanced automation
• Identify gaps in current reporting process and drive the implementation of new controls and strategic solutions
• 3+ years of data-mining and analytical experience, preferably in a financial services industry (can be 1+ or equivalent training if hiring an analyst)
• Strong PC skills in Microsoft Office; specifically Excel and Powerpoint
• Proven experience working with SAS to extract and manipulate data
• Bachelor's degree, preferably in a quantitative field
• Experience with Unix and shell scripting
• Knowledge of Essbase
• Strong data management and problem solving skills
• Ability to plan and execute in a timely manner with an appropriate sense of urgency
• Ability to manage multiple initiatives simultaneously
• Infer operational insight from statistical analysis and communicate complex solutions in a clear, understandable way to non-experts
• Prepare presentations and clearly communicate findings from initiatives to senior management and to the broader organization
• Create visualizations to make data easily accessible across the organization
• Own detailed analytical projects, create automated business intelligence solutions, and act as a resource for Regional Leader in complex analyses and data projects
• Understand difficult business problems and fully prototype data science solutions (back-end database, model and simple front end)
• Support new client acquisitions and integrations
• Ensure continued high quality of ad hoc performance reports and analytics, serving both to drive WCS SLT thinking and respond to requests from Global GE Businesses
• Bachelor's degree in Maths, Statistics, the Physical Sciences, Operational Research or Computer Science, or a relevant degree with quantitative analysis
• A minimum of 3 years relevant experience
• Must submit your application for employment through gecareers.com to be considered (Internals via COS)
• Must be willing to comply with pre-employment screening, including but not limited to drug testing, reference verification, and
• Preferred experience with technologies such as SAS, R, Hadoop, or any other analysis tools
• Preferred experience with Business Objects, SPOTFIRE, OBIEE or SQL Business Intelligence tools
• Experience of working in a global team
• University Degree. Preferably Computer Science or Business degree
• 10+ years of proven experience in data analysis, business analysis, data management, data warehousing, data transformation, metadata and reference data
• Possess excellent documentation skills and organizational skills
• Possess strong analytical ability to understand business data requirements and translate it to design concepts for data model development
• Proven experience in producing data requirements and conducting data analysis that have enterprise-wide data coverage in a large transformational program
• Experience in SQL query techniques and use of SQL tools
• Knowledge of conceptual and logical data model concepts
• Knowledge of dimensional modeling, relational databases, data warehouse and business intelligence concepts
• Financial Services Industry business knowledge preferred
• Experience in conducting data analysis using data profiling tool
• Experience in identifying business keys to use for reconciling data to authoritative sources
• Solid understanding of data domains in Financial Services industry
• Good understanding of front-to-back functions and data flows within an organization
• Good understanding of data and functional processes within Risk Management and Finance
• Proven expertise in data requirements documentation and data analysis
• Excellent understanding of data representation via data models including XML and related technologies
• Work closely with game designers to understand current and new features in order to identify & define in-game development and BI hooks, events
• Based on the identified hooks, write complex set of SQL queries in order to extract and analyze big, complex, multi-dimensional datasets with variety of tools
• Own instrumentation of analytics and tracking hooks during development phase; establish best practices for repeated application
• Generate actionable reports and recommendations on features that will improve retention, monetization and acquisition. Identify pain points and work with product management, design and product development to implement strategies to address key problem areas
• Share insights with executive leadership and game teams regularly. Create cogent reports that are simultaneously data-rich and easily digested
• Work closely with development, DGS BI and QA teams to make assure timely implementation and sanity of the identified BI hooks, events, data warehouse tables and etc
• Work closely with the game designer and producer to create, balance, and optimize the game
• Works with the project Business Analysts and LOB determine requirements for data
• Identify and assess potential data sources
• Recommends appropriate scope of requirements
• Defines business rules to map data into Data Supply Chain’s Organize or Consume layers
• Works with ETL and/or Data architects to translate requirements into technical data specifications
• Deliver on expectations while also managing/meeting the Enterprise Data Strategy/Vision
• Partnering with the Line of Business and application SME’s performs business rules and data mapping
• 7+ years mapping data using data profiling\discovery tools
• Strong interpersonal and communications skills
• Ability to translate business requirements into technical data requirements
• Knowledge of KeyBank data and its uses in the line of business application areas
• Knowledge of key data processes in the Data Supply Chain
• Strong SQL Skills and knowledge of data warehouse principles including an understanding of Entity-Relationship
• Perform data validation, data extraction, data testing and data loading in various applications for any data anomalies
• Perform in-depth analysis of data issues – issue resolution, root cause analysis
• Review designs, codes, process/test plans, or documentation to pertaining to data flow / quality
• Provide or coordinate troubleshooting support for data quality issues
• Prepare functional or technical documentation
• Work across all components of in-scope applications, e.g. input data reception and loading (fact and reference), dimensions mapping and derivations, aggregations, data delivery reports/tools refresh and transport
• Prepare reprocessing/data recovery plans – together with other functions
• Maintain internal and external communication of data quality incidents
• Bachelor degree in IT/Engineering/Math courses
• 3 - 5 years of experience in IT or support field, specializing in enterprise data warehouse
• Troubleshooting, problem solving and analytical skills
• Hands-on experience in any of the following: SQL, PL/SQL, SAP
• Excellent in verbal and written communication; ability to bridge technical and business issues
• Team player, self-starter, can work with very minimal supervision
• Knowledgeable in ITIL processes/ISO20000/ISO27000/CMMI/EDGE
• Execute detailed back-end analysis, trending, forecasting and recommend changes to improve marketing effectiveness
• Identify gaps in the data capture strategy and collaboratively implement enhancements across the organization
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Create automated dashboards and regular reports of digital marketing initiatives
• Collaborate across the organization to generate ideas and strategies based upon data-driven insights and recommendations
• Ability to work flexibly and efficiently:projects vary in length and are very fast-paced, must be comfortable adapting approach to fit the project’s needs and constraints; must exercise a balance between design/inspiration and academic research rigor in order to move quickly from planning, to conducting analysis, to synthesizing insights, to recommending directions and opportunities
• Complete command of Excel (an Excel skills assessment will be provided at time of interview)
• Strong analytical and strategic thinking skills
• Comfortable with ambiguity, able to multitask and prioritize competing responsibilities
• 60% Data Analysis and Visualization
• Coordinates integration of multiple, disparate data sets, reviews data for anomalies, investigates to identify cause, corrects data inaccuracies and inconsistencies, and determines the best approach for analysis
• Data analysis from multiple sources and assists in interpretation of results using a variety of techniques to uncover insights
• Provides recommendations and conclusions gained from analyzing data
• Determines appropriate format for data and results presentation
• Produces visuals (infographics, graphs, tables, charts, etc.) that make complex data easy to understand
• Coordinates ongoing production of reports that effectively present and summarize data (e.g., service and resource dashboards) to review by leadership
• 30% Analytics Project Coordination
• Gathers data and information from key stakeholders to inform the development of projects
• Performs assigned data collection and analysis, facilitates resolution of issues with guidance from the Sr. Data Manager, and reports status on project plans and progress at regular intervals to leadership
• Tracks the changes that occur to the project and associated documentation
• Create and report on the state of the Premium Ad Experiences business by establishing and tracking KPI’s, insights and reports
• Dive into our Native Advertising solutions and develop reporting and insights
• Provide front line reporting support by compiling data and performance reports, conducting campaign analyses, and conveying results to customers, internal teams and execs
• Troubleshoot and diagnose campaign reported metrics and reporting bug or issues
• Identify gaps and enhancements to campaign metrics and reports as well as business reports/dashboards leading to product requirements
• Develop insights on advertiser performance, product trends and operational health to drive product evolution
• Generate and maintain APX benchmark reports on our data for internal and external release
• Partner with marketing and research teams to develop meaningful metrics for inclusion in sales material and education as well as externally facing messaging/PR
• Work closely with APX Reporting systems to provide detailed product requirements and enhancements to continually improve our reporting products
• Partner with AOL & other analysts on monthly and quarterly business reporting
• BA/BS in a related discipline (e.g. sciences, engineering, economics, accounting, computer science, business) and/or 5-7 years related work experiences
• A strong understanding of digital advertising marketplace, including advertising performance, Viewabilty and revenue is desired. Familiarity with other Rich Media advertising metrics and tools a plus
• Experience querying, manipulating large data sets and creating custom data views and reports Track-record of business results driven by candidate’s data analysis and insights
• Expert analytical skills leveraging tools such as Excel, Tableau, Qlikview, SQL, Hive
• Demonstrable presenter and communicator with ability to tell stories with data and drive comprehension of results to various levels of the organization from sales to executives
• Ability to identify analytically-driven insights and translate to actionable recommendations for Marketing, Sales and Product organizations
• Strong communicator who can partner with a diverse set of technical and non-technical stakeholders and provide them with best in class front line analytical support
• Extremely organized and capable of managing, tracking and troubleshooting multiple projects simultaneously in a fast paced environment with multi-disciplinary teams
• Exceptional attention to detail balanced with creative and innovative approaches to problem solving Motivated and practical self-starter with continued thirst for learning
• Someone who is personable, passionate, fun and fits in with AOL culture
• Work with the Business Analytics team to build quantitative models for Assurance Services. Scope includes data preparation, data profiling, building models, writing white papers, visualization and presenting to the business audience the practical implications of the results
• Build predictive models using statistical and data mining methods in the areas of audit risk, staffing needs for engagements, monitoring, and other areas; principal investigator on other analytics projects
• Translate the results of the quantitative models into practical business implications
• Ability to think outside of the box and to learn new approaches to modeling business problems with a focus on the practical application of the results
• Develop and propose new analytics ideas about our markets, services, competitors and regulatory environment. Your recommendations should advance thinking on critical issues, and ultimately impact firm strategy
• Conduct high quality analytics work with the Business Analytics team. This will include developing leading practices for all phases of the analytics development cycle
• Establish leading practices for key analytical processes, including model development, visualization, and implementation, to enhance the performance of the organization
• Communicate progress, barriers, risks and benefits to clients, to achieve project success
• Gain a broad understanding of business fundamentals, and of the organization, both globally and in the Americas
• Be proficient in SQL and SAS (data manipulation); proficiency in Tableau highly preferred; knowledge of other programming languages is a plus (e.g. VBA; SAS JMP))
• Ability to understand key capital market and economic issues, as well as other business trends that could impact the firm
• Awareness of threats and opportunities facing the profession and the firm
• Comfortable in a rapidly changing environment, with competing and shifting priorities
• Strong project management skills and experience
• Ability to partner with other departments or with Area leaders
• 2-4 years experience working with data and data analytics
• Work closely with marketing teams to define key metrics, identify trends and opportunities across channels, campaigns and consumer segments, and provide solutions for their analytic and KPI requests
• Manage business needs for web analytics and tracking
• Develop and maintain dashboards based on KPI’s of the business
• Develop ad hoc reports based on business questions
• Develop and implement tagging/ web analytics code to enable tracking of online properties to ensure tracking is in place to allow for us to optimize consumer experience as well as allow for the analysis of the consumer journey
• Document all data standards and processes as appropriate and audit when necessary
• Manage internal and external resources to drive web analytics projects to completion
• Support A/B and multivariate testing efforts, from ideation to execution to post launch analysis
• Contribute to web analytics roadmap
• Engage in "root cause" analysis to assess changes in metrics and underlying causes and provide recommendations for improvement
• Assess the impact of various initiatives and measure results. Provide recommendations for improvement as necessary
• Analyze websites data on traffic sources and patterns and conversion funnel ; provide actionable insights to marketing teams on campaign analysis, customer segmentation and profiling; expand real-time analytics practice for high profile campaigns and new product/ content launches
• Create, manage and distribute data and insights via regular and ad-hoc reporting utilizing analytics tools and reporting/analysis platforms (Microstrategy, Tableau, SQL, Excel, …)
• Bachelor degree in a technical or quantitative discipline (Mathematics, Economics, Statistics, Computer Science, Engineering), Master’s preferred
• 5+ years related experience including hands-on expertise in performing and delivering quantitative analyses
• 3-5 years online marketing experience preferably in the web analytics space
• Experience with Adobe Analytics (Omniture) Site Catalyst
• Experience with Site Catalyst implementation
• Experience in web analytics requirements gathering, solution design and implementation; solid experience in the area of online visitor intelligence / behavior, tracking/tagging
• Experience with Ad Hoc Tool and Report Builder
• Experience developing dashboards based on business KPI’s
• Ability to derive insights from data
• Handle fast-paced and challenging job demands
• Self-motivated & analytically curious
• Strong quantitative skills, and experience utilizing scientific analytic methods, qualitative methods, and quantitative analysis techniques
• Tag Management solutions knowledge a plus
• Ad Serving platforms (Double Click, Ad Tech, Atlas, …) knowledge a plus
• In depth knowledge of SQL and Excel; programming experience and knowledge of Tableau a plus
• Experience with e-commerce and attribution modeling a plus
• Conduct advanced analytics and consumer segmentation using applications such as SAS or SPSS in order to maximize the effectiveness of digital communications and drive marketing strategy
• Create, manage and regularly distribute critical marketing-related reports utilizing relational databases and reporting technologies such as Microstrategy, Cognos, SQL, Excel, and Access
• Leads the design and development, in partnership with IT, of Business Intelligence platforms
• Ensure compliance with Data Management Laws
• Must have thorough understanding of database structure
• Experience creating complicated reports including sub-reports, parameter based reports, graphical reports, formula based, well-formatted reports, drill-down reports, analysis reports, etc
• 4+ years prior hands-on experience with database and/or digital marketing data including querying, reporting and analysis required
• Assist in the development, documentation and implementation of timely, relevant and comprehensive CCAR Y-14 Regulatory reporting requirements
• Analyze commercial and consumer loan and portfolio data, advising management of trends and any significant changes in the quantity and quality of the data elements being reported
• Perform prescribed analysis and ad hoc portfolio monitoring/reporting activities as assigned
• Strong analytical skills and knowledge of real estate,loans, leases, securities, and/or derivatives required
• Strong natural affinity for structuring and organizing large amounts of data in order to satisfy continually evolving reporting needs
• Be an active participant in managing the Systems and Data Analytic teams work items, including ad hoc research items and incidents on behalf of the GRC group
• Bachelor’s degree (B.A. /B.S.) from four-year College or University; or minimum 5 years related experience and/or training; or equivalent combination of education and experience
• Ability to research and review data conditions and translate them into recommendations, then contribute to the development and implementation of appropriate technical solutions
• Experience with SQL as a tool to research and identify data conditions within EDS Applications, systems and processes
• Drive the build out of DPM’s analytical capabilities by developing accurate, dynamic and visual reporting that clearly communicate trends, statistically significant anomalies and explain variances from the norm
• Provide analytical support as the primary contact for DPM’s Research capability using financial modeling techniques in excel and/or specialized tools for DPM. DPM provides enhanced data analysis for Participation, Residuals and Audit through identifying and resolving data exceptions and miscoding, correcting the data and, in some instances, working with MIS to implement solutions
• Manage the status and operational metrics reporting and indentify areas that need escalation to ensure progress. Analyze the reported metrics to identify trends and provide suggestions on how to improve primary analysis within Participations, Residuals and Audit
• Facilitate system enhancements during requirements gathering phases and user acceptance testing phases. Coordinate DPM development activities across the DPM team members
• Identify and document areas for process and data improvement as it relates to revenue and expense data from the distributing and production business units. Work with other members of the DPM team to implement these suggestions
• Provide high-quality data analysis and analytical solutions that support business objectives
• Identify actionable insights, suggest recommendations and influence the direction of the business by effectively communicating results to cross functional group
• Present data with an intelligence awareness of the potential privacy risks of the insights
• Use statistical techniques to create scalable solutions for real business problems
• Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation and model implementation
• Be aware of data sources within and without the company that could be used to complement current and future projects
• Provide thought leadership and dependable execution on diverse projects
• Identify emergent technology trends and opportunities for future growth and development
• M.S. or Ph. D. in a relevant field, such as Applied Math, Statistics, Computer Science, Physics, Economics, Electrical Engineering, or Bioinformatics
• Possesses excellent numeracy and understanding of advanced analytical techniques
• Versed in statistical analysis packages, e.g. SAS, R, RAT, SPSS
• Demonstrated experience in Data management tools; relational databases e.g. Oracle, Teradata, SQL Server), Data Manipulation tools, e.g. DataStage, Informatica
• Working knowledge of Big Data/Analytical technologies, e.g. Hadoop, MapReduce, MongoDB, Oracle Exalytics
• Superior communication and presentation skills, both written and oral
• Financial Services experience, preferred
• Strong use of databases/technology skills
• Experience in customer journey analytics
• Knowledge of tools, programming language and systems to automate, visualize customer journey
• Must be skilled at extracting data from multiple databases & languages
• Expert knowledge of SAS and SQL programming
• Must be able to extract data from appropriate sources in a complex warehousing environment; Requires in-depth knowledge of databases and business data elements
• Must be able to perform complex data processing (e.g. merging, sorting, data transformations) using SAS, SQL, or other ETL tools on PC
• Experience working with very large data sets (Big data) and extracting meaning and insights from this data
• Demonstrates an intermediate to advanced ability to perform mathematical calculations and analysis
• Must be able to use a customer centric approach in all work, and be able to relate tactics to overarching strategy
• Candidate must possess good communication and interpersonal skills in order to interact with various levels and functional groups
• Must be proactive, flexible and adaptable, as priorities can change quickly in a fast paced environment
• Must be excellent at managing time and projects, and mitigate project risks effectively
• Must be willing to take initiative and share ideas openly with Engagement Lead and other team members
• Can develop and produce routine and non-routine reports and analysis of intermediate to complex scope
• Interpret reports, providing analytical commentary and recommendations for change through actionable insights which drive measurable results
• Advanced: Excel, Word, PowerPoint
• Basic: Access, Visio, Project
• Participates in interview, hiring activities and decision making process
• Passionate communicator, able to clearly articulate
• Provide support and guidance to other team members
• Support business partners in solving the manufacturing process or supply chain challenges through the simulation work
• Develop and deploy new predictive and prescriptive analytics software and processes
• Collaborate with design, logistics, manufacturing, purchasing and supply chain groups
• Exhibit strong planning and organization, outstanding initiative, and a comprehensive knowledge of Caterpillar Inc., its products and services; its internal systems, processes, and procedures; and the external environment in which it competes
• Applicants must have a Master’s degree in Mechanical Engineering or Industrial Engineering from an accredited program with at least 3 years of industry experience in process optimization, design exploration technology, and statistics or data mining
• At least 2 year of industry experience in applying discrete event simulation for logistics, test or manufacturing facility
• Applicants must be proficient with Python, R or similar data mining language
• Applicants must be proficient with Flexsim or similar discrete event simulation package
• Applicants must have good knowledge of manufacturing processes, operation and supply chain
• Applicants must be proficient with Design of Experiment techniques
• Proficient with MS Access or similar relational database and SQL
• Proficient with Tableau or similar business intelligence visualization package
• Familiar with algebraic optimization algorithms such as linear and integer programming
• Familiar with earthmoving industry and its products and processes
• A self-starter
• An effective communicator
• Masters or advance degree preferred (statistics, computer science, data research), however additional years of relevant experience with a Bachelor’s degree will be considered
• 4+ years transactional fraud, rules-based analytical work experience
• Previous experience using Accertify platform and writing rules within preferred
• Previous experience creating & modifying iLog rules preferred
• Successfully completed Bachelor’s degree
• Three years or more of development or similar experience
• Three years or more of analytic or similar experience
• Familiarity with Oracle, SQL Server and SAS
• Preference for working in a team environment
• Successfully completed MBA or related Master’s degree
• Experience working with large-scale datasets
• Familiarity with Big Data solutions (including Hadoop and Greenplum)
• In this specific role you will be part of an integration team that explores the drivers of ABC and ABC Family digital video content consumption and works with the business to build and maintain statistical models in support of Ad Sales and Research
• This position will dig into forecasts and historical data to provide business insights and ensure accurate and timely forecast updates of ad inventory
• Experience with SAS toolset and programming
• Experience with data mining and building insights using large data sets
• Experience translating complex problems and solutions to all levels of an organization
• Ability to develop clear and concise thoughts into proposals, recommendations and findings
• Proficiency acquiring, organizing, cleansing and manipulating large amounts of data
• Demonstrated experience performing exploratory and quantitative analysis
• Experience with advanced modeling and data mining techniques
• Four plus years experience with SAS tools (e.g., Base, Enterprise Guide, Enterprise Miner, etc.)
• Four plus years experience with SQL
• Previous experience working with digital media data
• Knowledge of granular digital usage and delivery data (e.g., Omniture, DoubleClick, FreeWheel, etc.)
• Bachelor's degree in a quantitative field or equivalent
• Provide unified analyses of media, social, website and other data from sources such as ad servers, social listening and tracking tools, web analytic tools, client databases and third party data providers
• Regularly use SAS and SPSS software for analysis and Keynote or similar software to present
• Provide modeling, datamining and statistical analysis, as required on accounts
• Develop data capture business requirements, including page tagging recommendations and hierarchy
• Stay current with client and industry benchmarks
• Work closely with account team to make specific and actionable client recommendations
• Foster relationships with Account, Production, UX, Media, Creative and Technology teams
• Assist in delivering tracking analysis and reports to support client campaigns, programs, and platforms
• Recommend marketing tests and solutions as needed
• Deliver models and other advanced statistical solutions to client business case and marketing issues
• Assist analytics team in developing tracking and reporting requirements, particularly web analytics, social media, paid media
• Collaborate and work well with others
• Contribute to increasing the level of innovation in data, analytics and CRM at the agency
• 3 years + experience in a related role
• Strong analytical skills, must be proficient in analyzing and interpreting internet-related data from standard software packages, SAS and client databases
• Experience with web analytics packages such as Google Analytics, Omniture and Webtrends
• Expert user of Excel, SAS and SPSS
• Solid understanding of the fundamentals of digital advertising and social media
• Role requires the ability to write clear and concise presentations for client summarizing data insights, outcomes and implications in straight-forward and enlightening way for clients
• Agency background with interactive and/or direct marketing experienced preferred
• Data visualization experience a plus
• Support the global management of Client reference data for Capital Markets
• Provide robust data analysis and subject matter expertise that supports daily operations and enterprise initiatives
• Interface with internal and external clients and vendors as they relate to the client data management
• Solid understanding of data management practices
• 4+ years of data management experience in a similar role within the investment industry
• Advanced Excel Skills
• Ability to write and create advanced formulas using VLOOKUP, Arrays, Index and Match functions; debug and audit
• Build macros using VBA (Visual Basic for Applications)
• Ability to structure and present data for reporting using conditional formatting, tables and charting
• Intermediate SQL skills
• Work in a team environment and serve as technical/data subject matter expert for multiple business units and projects
• Prepare analyses and presentations of service and product reviews, including risk and compliance exposure
• Serve as a liaison/expert resource for both front office and technology business partners
• Perform ad hoc analyses; participate in special projects
• Research and document data sources and impacted targets creating end-to-end process rules & flows
• Develop code and/or procedures for repeatable data retrievals summarize by desired groupings
• Prepare analysis and presentation of periodic service and product results including metrics compared to quality targets
• Recommend methods to improve the use of data within specified areas as well as across the enterprise
• Mine data to perform ad hoc analysis and participate in cross functional special projects
• Understand business process management and business requirements of the customers and be able to translate to BRDs, data mapping specs, and create business cases for UAT
• Help to insure that the data governance standards are adhered to maintain and support data integrity
• Help to insure that compliance initiatives are adhered to including storage of artifacts, traceability, version control and change control
• Bachelor's degree in Computer Science, Actuarial Science, Finance, Math, Economics or related discipline required
• 3-5 years of requisite experience
• Minimum of 2 years’ experience working in business architecture
• Technology proficiency in Visio, SQL, BI analysis/visualization tools, and MS Office products - Excel, Power Point, Word and Access
• Demonstrated ability in data profiling/data forensics and lineage mapping, identifying and summarizing financial data and service delivery methods to generate business insights
• Effective verbal, written and presentation skills. Ability to “tell the story” associated with analysis for business partners at all levels of the organization
• Master’s degree desirable
• Experienced in data mining and dashboarding
• Experienced in financial services industry, preferably in an Asset Management capacity
• Skilled at writing code and SQL queries; familiarity with data quality/reconciliation tools desirable
• Flexible and adaptable to fast paced, changing environments; detail oriented and driven
• Manage and execute projects that are analytical in nature
• Develop analysis with related information and analytics and provide insights and commentary to executive level management that provides a basis for action
• Work with large amounts of data and analyze it to find conclusions
• Communicate complex ideas and translate data into an understandable document. You will need to be able to write and speak clearly and effectively and be able to create and present your own presentations to an executive team
• Bachelor's degree in Business, Economics, Finance or similar required, MBA strongly preferred
• 7+ years experience performing business or operational analytical functions
• Advanced to Expert level Excel, Access or SQL skills
• Advanced to Expert level PowerPoint skills
• Demonstrated financial modeling experience
• Financial Services or Broker/Dealer industry experience strongly preferred
• Business Case Analysis development and/or consulting experience is a plus
• Ability to evaluate and provide solutions to complex situations and problems
• Very strong analytical skills coupled with effective verbal and written communication ability
• Effective team player
• Desire to learn and grow as well as help others learn and grow
• Ability to present complex information in a clear and concise way
• Enthusiastic, positive attitude
• Customer service and / or operations knowledge or experience is a plus
• Demonstrated ability to interact with and influence senior leaders
• Take part in all activities associated with the measurement, analysis and reporting of relevant products and platforms
• Execute sophisticated quantitative analyses that translates data into actionable items and projects
• Interpret, document and present data-driven commercial insights to support business decisions relating to the performance of the platform and the products that comprise the platform
• Using analytics to identify inefficiencies in the current business model and implement in conjunction with relevant managers solutions to these inefficiencies
• Interpret, document and present data-driven commercial insights to support business decisions relating to the management of clients so as to ensure increased longevity, transactional behaviour and profitability
• Create new metrics to measure behaviour relevant to the channel covering areas such as acquisition, conversion, retention and reactivation
• Communicate directly with other business leads and senior managers with a view to educating them about the data behind their business decisions and implementing change
• 30 %: Data Collection
• 40 %: Data Analysis and Report Production
• 30 %: Special Projects
• Prefer 3+ years of experience in areas such as risk/portfolio management and analysis, finance/accounting, information systems, real estate industry (sales, appraisal services, etc.), retail/commercial lending
• Strong analytical skills and knowledge of real estate, loans, leases, securities, and/or derivatives required
• Responsible for designing, modeling and supporting enterprise data modeling, primarily within their Domain
• Understands, interprets and documents the data needs of the end-user community. Designs and supports components of Domain data to support business data needs
• Develops and maintains an integrated logical data model, minimizing data element redundancy and maximizing the compatibility and usefulness of data
• Partners with DBAs to ensure that the physical data model is consistent with the logical data model
• Provides design logic for the development of data management standards, policies, and procedures
• Promotes the principles of data resource management and data sharing, reuse of databases and single source data strategy
• Implements data management processes according to guidelines and standards
• Designs operational data stores and data marts
• Proposes solutions that improve infrastructure functionality and performance
• Responsible for adhering to applications security procedures, change control guidelines and Sarbanes-Oxley IT and business requirements
• Bachelor's degree or equivalent work experience defined as 3 to 5 years
• 4 or more years of relevant IT work experience
• Proven track record of delivering commercially beneficial insights and analytics strategies to large businesses
• Numerically brilliant – both from a commercial and analytics perspective
• Strong data manipulation skills – ability to handle and process large data sets
• Demonstrable experience with Predictive Analytics, Econometrics, Forecasting, Segmentation, Cluster analysis as well as traditional large-scale data warehouse driven analytics
• Demonstrable experience of SAS, R and SQL with compelling track record of projects and results. Experience and expertise of SAS Demand Forecasting a plus
• Strong analysis skills – ability to extract key drivers from a vast variety of data and highlight insights, gaps, opportunities and recommendations
• Strong communication skills - effectiveness and versatility in oral presentation as well as solid business writing skills
• Good understanding of business intelligence, digital marketing, testing and optimisation
• Knowledge of digital media analytics and any web analytics tool (Omniture, Core Metrics or Google Analytics) preferred
• Knowledge/experience with any data visualization/reporting tool (Tableau, Qlikview, Spotfire, Microstrategy etc.) preferred
• Define, design and Deploy and adapt core data quality and governance processes and metrics. Trend issues, metrics and data quality errors for policy and standards
• Educate and influence all levels stakeholders on institutionalization of data quality solutions
• Conduct data profiling, analyze and summarize profiling results, and present profiling results to multiple business / technical stakeholders
• Recommend business rules that can then later be integrated into Enterprise Data Quality Solutions
• Develop / configure DQ tools (IDQ) for enabling prioritized DQ rules
• Evaluate, and document business rules and data quality issues for areas prioritized by WDPR
• Analyzes sources, targets and defines data flows and data management dependencies (Data Governance, Metadata Management, Data Quality)
• Produces detailed integration specifications, typically as source-to-target mappings, consistent with the high-level DQ integration design specifications
• Responsible for collaborating with the business analyst and integration designer to resolve gaps between the business requirements and DQ integration design specifications
• Validate that the business requirements are complete, consistent, concise, and achievable
• Coordinates with data modelers, integration developers and DBA’s implementing the solution
• Should have designed & developed multiple data cleansing and standardization scenarios using mappings & industry standard products
• Understanding of Oracle, Teradata database technologies and hands on knowledge of SQL
• Enterprise data management, integration, analytical, and data quality skills
• Extensive experience in defining, developing and managing data management solutions for Hospitality / entertainment industry
• Leading requirement analysis, system analysis, design, development, testing, implementation
• Managing a Tier 1 (mission critical) technical environment including; driving continuous improvement through managed metrics and change management
• Cross functional / organizational stakeholder management (business and technical)
• Owning and managing issue / conflict resolution; demonstrated problem solving and decision making skills
• Working effectively in a fast-paced environment as part of a high-performing research, delivery and sustainment team
• Communication - demonstrated strong written and verbal communication skills
• Interpersonal skills for building and managing strong virtual / physical team focused on delivering business results
• Hands on experience with AGILE solution delivery methodology
• Minimum 7 years of data management solution delivery and maintenance of, business application and data management experience
• Bachelor’s degree in Computer Science, Management Information Systems or related field or equivalent
• Demonstrable experience with Customer Analytics eg Predictive, Segmentation/Cluster analysis. Econometrics/Forecasting exp welcomed
• Demonstrable experience of SAS and SQL with compelling track record of projects and results. Experience and expertise of SAS Demand Forecasting a plus
• Knowledge/experience with any data visualization/reporting tool (Tableau, Qlikview, Spotfire, Microstrategy etc.) preferred as well as MS PowerPoint
• Development of senior management presentations and facilitation of initiative approvals
• Coordination with external stakeholders to ensure adherence to stated targets and implementation of new policies and procedures
• Responsible for the overall project reporting (pipeline, status) and ability to analyze real estate data and being able to interpret and present findings to senior management
• Must be assertive and diligent in obtaining accurate results
• Track and Report CRS Productivity and Reserve schedules
• Must have 4+ years of experience in a finance / accounting related function
• Must have working knowledge of basic GAAP accounting
• Demonstrated leadership skills – proven ability to lead teams through changes in systems, processes and procedures, while successfully achieving key goals and objectives
• 10+ years of experience in financial industry & information technology
• 7+ years of experience as data analyst in investment banking
• Strong data analysis and data profiling skills
• Strong SQL writing against DB2, Sybase and other RDBMS
• Subject matter expertise in key data concepts like Trades, Positions, Allocation, Client, Account etc
• Experience in documenting data flow diagrams, ETL Mappings, Data Dictionary, Metadata and Data Quality rules
• Strong collaboration and communication skills-
• Experience in an Enterprise Data Architecture environment and has end to end understanding of data processing life cycle
• Understanding of data model and data warehouse concepts
• Knowledge of Informatica ETLtools, Informatica DQ tools, Unix and Autoys is plus but not required
• Compliance domain experience and understanding of compliance process will be a plus
• Self-starter with the initiative to identify and act upon opportunities with little to no direction
• Support business analysts and developers with data subject expertise, query building and optimization
• Translate business requirements into ETL design specifications
• Write and maintain ETL mapping specifications for development team
• Identify and document DQ rules and metrics
• Interact closely with Business Analysis team, ETL team and BI Reporting teams to ensure understanding of proper use of data
• Coordinate and conduct impact analysis because of upstream data changes
• Knowledge of financial services
• Strong SQL writing
• Strong analytical, profiling and troubleshooting skills
• Informatica Data quality (IDQ)
• Unix & Autosys
• Power Designer or CA Erwin
• BI/data visualization tools: Qlikview, Tableau or other
• Data Quality – Identifies and produces regular or ad hoc reports on data quality issues and in-depth data analysis with requisite plans to remediate issues
• Data Management requiring detailed subject matter expertise on the operations of all tools used in data stewardship tasks, including data repositories, data maintenance applications, reporting tools, and data quality issue tracking systems
• Will work with IT Integrators to ensure that tools and data structures provide the functionality required to perform data management and data quality tasks
• Root cause analysis of all data quality problems with follow-through to resolution
• Understanding of data quality concepts and ability to drive quality initiatives
• Experience of working in a high pressure support environment dealing with senior individuals on occasion
• Knowledge of the Enterprise Architecture functions and a sound understanding of the IT functions required to support it
• Understanding of data analytics and tools
• Experience in working with Global Teams across Geographic locations
• Experience of application/platform monitoring and knowledge management tools
• Basic understanding of Microsoft SQL server/ SQL language
• Windows/ Microsoft Office Suite
• Ability to develop strong working relationships
• Self-starter with ability to take the initiative and master new tasks quickly
• Able to work independently, and as part of a team
• Proactive problem solving experience, using judgment to make decisions where no clear precedent may exist
• Strong organization and prioritization skills
• A flexible approach to working hours
• Good Attention to detail
• Good English verbal & written communication, inter-personal and facilitation skills are essential to succeed in this position
• College degree or professional 5 - 7 years' work experience
• In lieu of a Master’s degree, or foreign equivalent, and three (3) years of professional experience, employer will accept a Bachelor's degree, or foreign equivalent, and five (5) years professional experience, post-baccalaureate and progressive in nature
• Demonstrating Strong EQ (Be Aware) – Having a keen sense of self-awareness is the foundation of leadership at Adobe. Whether you’re an individual contributor or a people manager, you’re someone who’s empathetic and mindful of your impact on others
• Selecting Talent (Be a Recruiter) – You’re a guardian and an ambassador for selecting talent at Adobe! You recommend and recruit only the best. You embrace diversity of ideas, experiences and working styles because you know that diverse teams drive better business results
• Role Modeling Check-In (Be a Coach) – We don’t believe in annual reviews and rankings. That’s why, feedback flows constantly at Adobe. To succeed, you’ll meet frequently with your manager to receive ongoing feedback, set challenging performance expectations, and pursue continuous development opportunities
• Scaling the Business (Be an Owner) – You approach your role as if you own the business. The buck stops with you. Your goal is to always deliver an exceptional customer experience by listening to feedback and continuously looking to improve efficiencies
• Establish leading practices for key data and reporting processes, including validation, visualization, automation of processes for building reports, development of quality control procedures and documentation to enhance the performance of the organization
• Develop complex queries in SQL Server to automate data validation efforts. Supervise and train a junior data analyst in the development of such queries
• Work with the Audit Risk Analytics team to build reports for the Analytics efforts of the ARA team. Scope includes data preparation, data validation, designing efficient/interactive processes for report building, visualization, documentation and presenting to the ARA team of the results
• Use modern reporting and visualization tools to help translate the results of models and metrics and other analytics outputs for the business audience Ability to think outside of the box and to learn new approaches to reporting business problems with a focus on the audience and implementability
• Communicate progress, barriers, risks and benefits to the team and the partners, to achieve project success
• Be proficient in SQL and a visualization tool (Tableau or Spotfire); a working knowledge of data manipulation in SAS is a plus
• Ability to supervise a junior data analyst
• 2-4 years experience working with data and visualization tools in a business context with some supervisory experience
• 3+ years of relevant experience
• Bachelor’s Degree in Computer Science, Computer/Systems Engineering, Economics, Mathematics, Statistics, or a related field
• Experience analyzing and interpreting data, maintaining and managing large datasets and ensuring the integrity of data
• Working knowledge of Access, Alteryx, Excel, SAS, SPSS, SQL queries, Tableau, VBA, and XML
• Manage the planning, development and implementation of various projects and initiatives in support of the department and/or division. Develops project plans ensuring activities to be performed, estimated time frame and effort, and other pertinent information is covered. Manage the day-to-day project activities
• Direct and monitor resources which may or may not include direct supervisory responsibilities, but rather participants’ project activities to ensure completion of project(s). Provide input to managers on project participants’ performance appraisals as requested
• May be responsible on an individual basis for directing the most complex, critical and highly visible projects for division and/or bank wide in size. Will facilitate project meetings and publish meeting minutes. Tracks issues and resolution
• Develop and produce complex ad hoc and automated departmental reports and spreadsheets to include but not limited to project or product strategy analysis, profitability, historical reporting, work flow analysis, and financial analysis
• Research and gather business and financial information regarding business results. Perform complex analyses to support business decisions. Provide feedback to management regarding results. Make recommendations on findings to management
• Design and implement complex and highly specialized PC based models to support business decisions, making recommendations to management based on research and financial analysis
• Develop a thorough and expert understanding of the business and its functions, processes and operations
• Keep abreast of business and market trends that may affect the business/department
• Serve as a member of the OCA Reporting & Analysis team, with a focus on continuously optimizing the Complaint Management Program (CMP)
• Primary owner of the Text Analytics model, and the keyword dictionaries to support the CMP programs
• Responsible for leveraging Regulatory Taxonomy Heat Map model to identify potential areas of concern, and performing advanced analyses that require integration of multiple data sources and business partners to complete
• Independently develop and direct a variety of more sophisticated fact-based analyses and ad hoc reports that aid Management in making decisions relating to Complaint data
• Responsible for formally communicating to Senior Leadership the periodic results and findings from Complaint data reporting and analyses
• Perform other assignments/projects as requested by management
• Bachelor's Degree, or in lieu of a degree a minimum of 4 years work experience
• Minimum seven (7) years relevant experience
• Minimum two (2) years demonstrated data analysis experience
• Advanced Microsoft Excel skills (ability to author macros, etc.)
• Expertise in Data Visualization best practices
• Seven (7) years banking industry experience preferred
• Knowledge of, and experience with, business intelligence toolsets (i.e. Qlikview or Tableau) as well as database management principles via Structured Query Language (SQL)
• Working knowledge of financial models
• Ability to interact effectively with all levels of personnel
• Excellent project management skills
• Periodical management reporting and graphical presentation of data analysis with focus on a broad range of products such as accounts, credit cards, mortgages as well as product bundles and other banking services
• Participating in product related projects to provide ad-hoc analysis and special deep dives in close collaboration with product managers
• Preparing and designing data sets e.g. for creation of product- and portfolio analysis
• Analyzing client behavior (client segmentation, discover patterns in data)
• End-to-end accompanying of tactical and rule based (multi-channel) marketing campaigns
• Supporting realization of pricing initiatives
• Creating business cases for decision boards
• Write queries and stored procedures in SQL, exports data into excel or csv files, reviews them for quality and data integrity, and send results to internal clients or external agencies
• Develop complex SQL queries against various data and computer sources. Including complex Sub queries, correlated queries, and nested queries
• Concisely summarize and communicate recommendations to various levels of management
• Analyze and interpret data, producing clear and compelling reports for different audiences which may include graphs and charts of data developed by analyzing situations and/or data models from which answers can be obtained
• Verify accuracy of data pulled and revises methods of data retrieval by following a standard process
• Provide data and respond to questions to external groups/agencies/vendors
• Propose report formats, including graphical presentations to effectively communicate meaningful data trends and relationships
• Audit and document existing and new data structures and data flow processes; provide documentation and training to reporting application end users
• Design and implement data quality monitoring reports, alerts, and processes
• Work with partners across Digital functions and LOB’s to provide data driven insights in support Digital strategic direction and growth
• Provide consultative support for Digital Product partners driven by fact-based findings
• Evolve and refine measurement frameworks and KPIs for Online and Mobile Customer Measurement
• Provide analysis and associated data visualization and story-telling
• Collaborate within Digital Analytics to enhance the quality and value of team deliverables
• Work with Data Services and Core Analytics partners to enhance overall performance of Digital Analytics team
• 5+ years relevant experience analyzing online and mobile customer experiences
• Demonstrated ability to define business KPIs and establish measurement frameworks
• Hands on experience with behavioral and transactional analytics tools and techniques
• Experience working with Business Intelligence (BI) platforms to deliver reports and scorecards
• Experience with Tableau, Adobe Data Workbench, and SQL preferred
• Ability to communicate effectively with executives, business partners, and technical resources in analytics and data management
• Post MBA Strategy and/ or Management Consulting experience preferred
• 5+ years of experience working with SQL Server Databases, and SQL; 5+ years of experience gathering business requirements
• Bachelor's Degree in Quantitative / Computer Science or a related discipline
• Certified Data Management Professional (CDMP)- Certification Programs from ICCP- Institute for the Certification of Computing Professionals
• Knowledge of the Banking and Brokerage industry (products and services)
• Understanding of database design and administration with AS400 Database knowledge of the Source System
• Microsoft Office/Suite proficient (Outlook, Word, Excel, PowerPoint, Visio, etc.)
• Superior mathematical skills
• 15+ years of experience working In Data Issues analysis and Cleansing projects with progressively increasing responsibilities in Data Management
• Certified Information Management Professional (CIMP)
• Experience in Pension Administration or Financial Services
• Providing oversight of regulatory, financial and post-exit contractual responsibilities
• Managing risk, operations, systems, and records management
• Identifying, developing, and managing analytics, including emerging trends and product demographics
• Business Analysis Responsible for conducting quality assurance reviews, analyzing business performance or experience and assisting in the completion of analysis projects, such as
• Validating service level agreement reports from TPAs for compliance with terms of agreements and obligations
• Assisting in developing test plans and performing operational reviews of TPAs
• Providing information and analysis to facilitate monitoring and drive the decision making process for internal and external customers
• Operational Product Support - Produce standardized reports, statements and invoices to support various products and subsidiaries, including
• Preparing transition service invoicing for successor owners of the business
• Preparing premium billing and anniversary statements to customers
• Responding to mortgage lien release requests and demutualization check reissues for Canadian customers
• Maintaining process inventories for management monitoring
• Regulatory Reporting File annual, quarterly and monthly reports with state insurance department and regulatory/government agencies. Assist with complying with new laws and regulations, such as the Affordable Care Act for health insurance
• Additional Work As Required
• Strong Microsoft Office Word and Excel skills for data manipulation and analysis
• Ability to understand business processes, analyze data and follow through to resolve issues
• Ability to foster and build relationships internally and externally across multiple departments
• Ability to manage ad-hoc projects and scheduled assignments simultaneously
• Undergraduate degree preferred
• Two plus years of data analysis/operational data experience desired
• Create and maintain high-level reporting systems using MS Access
• Develop and enforce database administration and user standards and procedures as well as oversee user security and database access
• Collaborate with business process owners to define requirements, then design, develop and deploy VBA applications to meet these requirements
• Troubleshoot and maintain various MS Access databases developed and utilized by our team to ensure optimal performance and data reliability at all times
• Complete various data-related projects as directed by the manager
• Evaluate, delegate and monitor completion of client or internal requests
• Complete and/or support more junior members in completing one or more of the following: provide second-level quality review of data processed by other team members; guide new clients through implementations processes from a data perspective; program and develop MS Access databases; improve and maintain data security; perform User Acceptance Testing of software releases; and participate in requirements-gathering during software development
• Demonstrate strong analytical skills as well as confident decision-making ability
• Be responsible for developing tools to streamline processing of data files being loaded to the system, reviewing data and determining its usability, and transferring this knowledge to less experienced members of the team
• Be responsible for supervising the work of and supporting 3-4 individuals
• Work directly under the manager of the team, and demonstrate ability to act independently and assign tasks based on the skill sets of the applicable individuals
• A bachelor's degree with an emphasis in accounting, finance, or related field and a minimum of 2 years of related work experience; or a graduate degree and approximately 1-2 years of related work experience
• Ability to train others on XML file transfer methods
• Familiarity with tax-related concepts
• Excellent verbal and written communication skills, organizational skills and strong analytical skills
• Ability to thrive in a team environment
• Capacity to work independently and effectively on a variety of tasks at the same time
• Commitment to following through on all client and internal requests
• Interface with internal and external clients and vendors as they relate to client data management
• Completion of an applicable university degree and/or relevant professional designation is require
• Experience with Excel Fuzzy Lookup
• Elicit and document business data requirements, risks and priorities to establish a clear understanding of the stakeholders’ environment in support of solution development
• Translate business requirements into source / target data mapping documents
• Profile and evaluate existing data using various sources and methods (SQL, EBCDIC, XML, etc.)
• Document environmental knowledge and leverage existing knowledge repositories
• Ensure the traceability of individual requirements and adherence to the defined requirements management process
• Analyze business requirements and perform current/target/gap/impact analyses
• Articulate business needs, gaps, impact across all areas and proposals to close gaps
• Validate that the proposed/designed solution(s) and associated testing approach will support meeting the articulated business requirements
• Prepare documents such as expected benefits, gap analysis, use cases, models, current and proposes process, workflows, data flows, implementation plans and end user guides in accordance with standards and methodologies
• Identify/escalate conflicts, issues and changes in order to appropriately manage scope
• Support achieving consensus on scope changes and achieve signoff by all stakeholders
• Investigate, evaluate and support prioritization of client requests for new or existing solutions
• Assist in defining business criteria for prioritization, and other key decisions (e.g., product evaluation or build vs. buy decisions)
• 3-5 years of data analyst / business analyst experience in the financial services industry
• Knowledge of pension / retirement recordkeeping industry
• Bachelor’s degree in computer science, information systems or business related field
• Experience working with dimensional data models and data integration concepts a plus
• 1+ years of prior experience with Hadoop application architecture a plus
• 1+ years of prior experience with Omniplus and/or Siebel a plus
• Bachelors degree or equivalent experience required
• Minimum 3-5 years experience in data analysis or related field
• Excellent analytical and problem solving skills with the ability to communicate analytical findings clearly and effectively
• Ability to drive positive change
• Ability to establish and build relationships across all levels and functions of the organization
• Strong communication skills with attention to detail
• Advanced Microsoft Excel and Access skills
• Experience with Tableau, Cognos, Business Objects and other data management tools is preferred
• Experience with relational databases and knowledge of query tools and statistical software is plus
• Able to pose hypotheses, challenge assumptions, and uncover best practices in data analysis
• Discover and manipulate data using a variety of analytical tools
• Excellent IT skills, including Knowledge of DB2, PostgreSQL and Jasper Reports or equivalent
• Able to write advanced SQL code
• Define and implement the people KPI framework in collaboration with the eHR department as well as the Finance department to generate actionable insights for management and provide a holistic approach towards reporting
• Act as a vanguard for eHR and the HR group by providing a filter for incoming reporting needs
• Develop and implement a dashboard for HR strategy
• Link people and capabilities data to the company's sales and finance data
• Understand the business issues and translate them into a data task
• Capable of presenting data back to the business in an easy-to-understand way
• Interpret human capital data and trends to ensure a mission-ready workforce
• Develop and maintain human capital data assets, reporting and management dashboards and analytical tools
• Conduct employee surveys and organisational assessments to support data-driven management strategies and strategic workforce planning objectives
• Identify, join and analyse disparate data sets and prepare briefings/recommendations to be presented at all management levels
• Possess an understanding of what information and products are valuable to senior executives, and how to best engage senior executives
• Excellent interpersonal skills, effective networking and forming relationships (especially towards other Data Analysts), interpersonal relationship development
• Ability to communicate effectively orally and in writing, excellent communication skills concerning the translation of business needs into data and vice versa
• Detail-oriented knowledge as well as a broad understanding of the business
• Ability to critically reflect and consolidate the demands of reporting, as well as the data problems of in-house consulting
• Strong analytical and conceptual thinking
• Ability to critically analyse an issue using database evidence
• Ability to analyse processes/issues and write reports
• Data analyst or data scientist capabilities
• Mix of analytical and coding skills and creativity and business know-how
• Ability and proficiency to extract and analyse data using a statistical tool (e.g. SPSS or SAS) and Excel
• Broad experience in the support of HR-oriented projects, such as strategic workforce planning, engagement surveys or diversity/female leadership quota
• Organisational representation and customer orientation
• Proficiency in writing non-technical reports and analyses
• Aptitude for data collection, numbers and attention to detail
• Bachelor's, Master's or PhD in industrial or organisational psychology or HR (minimum GPA of 3.0 or better on a 4-point scale is required)
• Work experience requirements: Bachelor's degree – 2 to 3 years, Master's degree – 2 to 4 years or PhD – 1 to 2 years
• Internship or studies abroad
• Experience in fields involving statistics; mathematics; computer or mathematical programming; survey research, design, and analysis; and modelling
• Experience in: human capital metrics and/or analytics, finance, accounting, compensation or an alternative quantitative function, inferential statistics, data visualisation, product development and testing, organisational development or internal consulting, Visual Basic programming, presentation and briefing techniques, manpower management background (manpower systems and processes, oversight organisations), knowledge of the Intelligence Community; measurement concepts/principles
• Proficiency with MS Office (Excel, Word, and PowerPoint)
• Tools: Tableau, SPSS, Microsoft Access or other relational databases, Lawson, Cognos
• Collect and analyze data to evaluate the performance of Blizzard web and mobile websites, mobile apps using tools like Google Analytics and in-house data systems
• Create, maintain, and propagate custom and recurring analytics reports and dashboards delivering insights on site performance, new features, user behavior, and testing
• Partner with program management, design, and engineering leads to define KPIs, metrics and analytics strategy for new and existing products. Participate in preparing, documenting and analyzing multivariate and A/B testing projects
• Present your research findings to teams, stakeholders, and executives to help support decision making
• Work with development teams to implement tracking tags and troubleshoot issues related to tracking and reporting
• Train and mentor team members in the use of analytics tracking tools and services (self-service model)
• Champion and advocate for the use of data and research in project execution across web and mobile
• Create product- and portfolio analysis
• Generating ideas based on data/statistical analysis
• Participating in projects to provide ad-hoc analysis and special deep dives in close collaboration with product managers
• Analyze client behavior (client segmentation, discover patterns in data)
• Data selection for tactical and rule based (multi-channel) marketing campaigns
• Support realization of pricing initiatives
• Creation of business cases for decision boards
• Work with TLT initiative teams to use their analytics skill set to identify and quantify revenue, margin, and SG&A improvements and other opportunities for key projects and initiatives
• Will build predictive and prescriptive data models and then present the business case for the value of these models. Some examples include predicting store performance after proposed operational changes, cross-selling opportunities between store banners and specifying potential savings after consolidating
• Provides analysis to working teams on TLT initiatives: Identify synergy values; Validate business cases; Provide ongoing analysis in current work steams
• Produce periodic and ad-hoc reporting as needed to support integration-related analyses
• Assist with creation of executive committee presentations
• Collect and analyze business and financial data to support the IMO in refining new value creation initiatives that support organizational goals
• Engage key stakeholders and clearly defines deliverables
• Consistent regular scheduled attendance is considered an essential function of this job
• Prior experience working in a system analytics and/or data warehousing environment is required
• Bachelor's Degree in field related to role
• Experience in business writing or creative writing desired
• Experience with financial analysis
• MS Office Suite including Access
• Identifying, analyzing and interpreting data to meet business requirements and facilitate development of next generation surveillance algorithms
• Building knowledge and understanding of transaction, reference and market data for specific asset classes
• Liaising with project/ development teams and providing support during program and project life cycles
• Interpreting data and analyzing results using statistical techniques to identify trends or patterns in complex data sets
• Identifying and documenting Critical Data Elements used in Surveillances, Research and Analysis etc
• Defining data quality rules for profiling for Critical Data Elements for data concepts like Positions, Trades, Reference Data
• Providing Level 3 support as required to resolve data issues and gaps
• Understanding current data processes and business requirements to help determine new and innovative ways to provide end-to-end solutions for compliance surveillance activities
• Experience as a data analyst in financial markets
• Good understanding of capital markets and trade life cycle and understanding of key data concepts like Trades, Positions, Allocation, Client, Account etc
• Strong knowledge of and experience with databases, SQL and analytical tools like Business Objects, Microstrategy etc
• Technical expertise in defining data models and data mining
• Strong analytical skills with ability to collect, analyze and disseminate large volumes of data with attention to detail, accuracy, and data quality
• Experience working with BIGDATA technology, relational DBMS,'(tm)s like Sybase, Oracle, SQL Server, Sybase, SQL etc
• Good understanding of database validations, constraints, syntax and data types
• Ability to communicate clearly and concisely, both orally and in writing with business and technology stakeholders
• Familiarity with project management, software development life cycle, excellent written and oral communication skills
• Project experience on a production implementation of Hadoop with massive data volumes
• Opportunity to work on the universe of traded products / assets across Citi’s Capital Markets businesses globally
• Potential to contribute to projects involving complex feature-based data algorithms and machine learning
• Exposure to surveillance functions in a dynamic and challenging industry with regular close collaboration with our surveillance portfolio clients
• A team with a win-together/lose-together attitude and strong sense of identity and positive culture
• Assist manager in planning, development and execution of Microsoft SQL Server and Tableau based data analysis procedures
• Consult with audit teams to provide data analysis support and guidance during audit engagement planning and execution
• Follow development and execution methodologies. Create sustainable and repeatable data analytics leveraging Microsoft SQL Server and Tableau platforms
• Assist in the documentation of functional, technical and source data requirements
• Act as project lead for automation and audit support projects. Inform manager, wider audit team, and Senior Management of project status, issues, risks and results
• Interact with management and business partners to identify appropriate data elements required for analytics. Apply professional skepticism when assessing data sources and validate completeness and accuracy of data received
• Provide support to the existing data analytics environment, including periodic data refresh, troubleshoot errors, fix bugs, and implement minor enhancements
• Demonstrate understanding of Visa's and Internal Audit's strategic vision, be a self-starter, and be responsible for actions promoting this strategic vision
• 5-8 years of data analysis experience, preferably leveraging Microsoft SQL Server or Tableau tools
• Demonstrated knowledge of the data analysis process and experience with the application of data analytics in the assessment of IT and business processes
• Experience with Microsoft SQL Server (SSMS, SSIS and SSRS), SQL/T-SQL Query Language and Tableau (or like tools) preferred
• Experience in developing data analytics and dashboards
• Strong time and project management skills
• Good analytical, organizational and presentation skills
• Ability to travel domestically and internationally approximately 10%
• MCSA and MCSE certifications in SQL Server, or Tableau Desktop Certification are highly desirable
• 3-5 years of internal audit experience preferred
• CISA and / or CISSP certifications a plus
• Design, lead, and execute analysis and effectively communicate insights
• Present findings of your analyses to mid-level managers and executives
• Gather and document analytics needs and reporting requirements
• Help answer the thorniest business questions including ones we didn't think we had
• Lead the development of automated reporting and dashboard prototypes for business users
• Identify data requirements for & collaborate closely with business stakeholders, including Product Managers and Data Warehouse engineers
• Work to tight deadlines and short turnaround times
• Elicit requirements from a various stakeholders and to distinguish between requests and underlying needs
• Work with large and complex data from a variety of sources across numerous database platforms
• Be able to work in collaboration with other analysts to balance competing priorities and deliver insightful analytics
• Advanced SQLknowledge
• Experience with database platforms Teradata, Oracle, SQL Server and MS Access highly regarded
• Advanced knowledge of Microsoft Excel
• Experience within Financial Advice is highly favourable
• Provides weekly, monthly, and annual reports. Provides special reports and analyses to support the business as necessary
• Supports efforts to maintain accurate master data. Extracts data and provides analysis of master and transactional data
• Conduct regular audits to ensure data integrity
• Identifies issues, analyzes available data and information, and recommends changes to management
• Creates and maintains multiple operational reporting tools
• Provides analytical support of actual results against budget and feasibility of proposed business strategies
• Consolidates data reports and delivers to help drive data-based strategic decision making
• Provides analysis prior to and following any recommended changes
• May create and maintain compliance reports that identify discrepancies within the Company's billing systems
• May conduct regular HRIS maintenance and audits to ensure the quality of data integrity
• May ensure that all employee records in the HRIS databases are accurately updated in a timely fashion
• Provides user feedback to management and helps influence future systems enhancements
• May provide guidance and direction on complex HRIS transactions
• Ensures accuracy of data through partnerships with team members. Provides day-to-day validation and spot checks
• May prepare reports to be used by other departments to correct billing issues
• Generally requires 5-7 years related experience
• Performs exploratory data analysis and statistical modeling in support of ongoing lines of research, aid in the refinement of existing tools and development of new tools, and fulfill ad hoc requests
• Works with a mix of data types (e.g., aggregate metrics, consumer-level data) employing creativity and flexible problem solving skills to address a variety of marketing questions
• Works independently and with other marketing professionals (Strategy, Account, Creative, Research) to express marketing and media questions as manageable analytical problems leading to valued decision support
• Plans, executes and effectively communicates the results of analyses to translate complex statistical results into insights and actionable business decisions
• Develop hypotheses, analytic designs, business cases and data requirements; Identify data definition and quality issues and help provide appropriate resolution
• Provides counsel to other analysts, Agency personnel from various disciplines (Strategy, Account, Creative, Technology, Production) and clients on how to employ statistical analysis to improve marketing results
• Strong background in statistical modeling and forecasting: some mix of expertise in generalized linear modeling, time-series forecasting, decision trees, machine learning, consumer segmentation, etc
• Proficiency in SAS or SPSS statistical packages, Microsoft Suite (Excel, PowerPoint, Word). Other software and language experience a plus. Ability to learn and employ new software and methodologies
• Experience developing and working with small to very large structured and unstructured data sets to develop analytic data files and to map results back into production environments
• Strong intellectual curiosity, critical thinking, and a passion for analytics
• Ability to work in fast-paced marketing and advertising environment both independently and collaboratively
• Ability to clearly communicate technical concepts in verbal, written, and presentation form to non-technical audiences
• Experience in the automotive industry a plus
• Graduate degree preferred or Bachelor’s degree with applicable skills and experience. Discipline is flexible but role requires strong quantitative ability and knowledge of the social sciences
• At least five years of applicable experience using SAS, SPSS and other tools for predictive and descriptive model development
• Data gathering, preparation, transformation and model development using tools such as SAS and MS Excel
• Design and Implement data models on an as needed basis
• Manage project workload and ensure that organizational data policy and standards are adhered too
• Provide on-going communications on project status and systems restrictions
• Act as the Global Compliance subject matter expert (SME) on "Big Data" technology projects
• Contribute to the ongoing development of the team by sharing information, knowledge, expertise and lessons learned on a regular basis
• Ensure high quality work and maintenance of standards within own area of responsibility
• Participate in project committees as necessary to provide guidance and support for technology and act as a key contact for specific business processes, projects or procedures
• Data Visualization and Analytic Diagram creation on as needed basis
• Develop data procedures and documentation as required
• Provide assistance, support and management of other projects as required
• Establish and maintain strong relationships with key internal and external partners including business and enterprise unit compliance groups', OCDO, Enterprise Data Stewarts and other key stakeholders
• Design and execute data processing tasks, including collecting source data, manipulating it as per requirements, and transmitting to third parties
• Verify accuracy and integrity of databases, files, and end products (direct mail, email, etc.), both programmatically and via visual inspection
• Respond to inquiries from clients, call center, and Account regarding participation, billing, and fulfillment
• Perform data quality control processes
• Design and execute data processing procedures to handle above tasks
• Perform ad hoc analyses, queries, or data manipulations
• Run a variety of reports and verify their accuracy
• Perform billing operations for the program
• Handle suppressions at multiple levels
• Maintain lookup tables and pre-load files, including synchronizing them with data from third parties
• Review weekly random sample proofs
• Generate and maintain seed lists
• Identify root cause for data-related issues from client, print center, and call center
• New development / enhancements
• Liaise with development, including formulation of system enhancement specifications and testing modifications
• Maintain business rules for print, email, and web sites as appropriate
• Design report templates for developers to program
• Develop reports for clients, Account, development, Call Center, and Data team use
• Develop and maintain imaging instructions for print center
• Test web site to ensure enhancements/new projects are manipulating and storing data accurately
• Create fulfillment files for proofs
• Create test files to test business rule and content changes
• Review results of tests
• Assist in other database marketing services work as necessar
• Recommend measures to improve work process methods, equipment performance, and quality of product, as appropriate
• Ability to work independently in a team atmosphere
• Strong analytical/math, presentation, and writing skills
• Ability to think logically/strong deductive reasoning
• Ability to understand and use quantitative and qualitative research studies
• Detail Oriented in a multi-task environment
• Bachelor’s degree or equivalent experience is required
• Minimum Two (2) years of relevant data analysis experience is required
• MS Excel experience utilizing VBA macros and Excel Automation from external programs is a must
• SQL – preferably on multiple Microsoft data platforms including Microsoft SQL Server and Microsoft Access is highly preferred
• Business Application Development, including requirements gathering and specification writing is required
• Experience involving Data integrity, QA and control is required
• Detailed reporting in a multi-task environment
• 3-5 years work experience in related field, preferably managing digital collectionsStrong database usage and ability to understand data structures
• Strong cataloging and description background
• Experience in Digital Asset Management
• Strong interpersonal skills, along with verbal and written communication
• Strong understanding of metadata standards and experience creating taxonomy
• Experience with media technologies and production workflows
• Detail oriented and organized
• Familiarity with learning and teaching new technologiesFamiliarity with Media & Entertainment industry
• Membership in industry trade organizations (ALA, SAA, SLA, Siggraph, etc.)
• Former Studio Technology Intern
• Lead the Information Technology (IT) data gathering for regulatory exam requests by liaising with IT staff to gather and finalize all examination request letter items in the IT section
• Project manage/support the creation of a searchable mechanism/database of data requests that would more efficiently facilitate data production
• Organize data into easily retrievable categories for exam readiness, business planning and regulatory response purposes
• Interpret exam data, analyze, and identify trends or patterns from the past exam data requests /issues and provide ongoing reports
• Work with business partners to develop and implement standardized data collection processes for the various entities
• Establish data reconciliation procedures and escalate issues to LOBs and CCOs for resolution when identified
• Implement strategies that will help us optimize data quality
• Keep abreast of new systems or changes on the business side of the enterprise to help direct us to the correct groups/individuals
• With admin support, facilitate maintenance of loaner laptops and related software, including by testing software, troubleshooting, and liaising with responsible IT staff
• Knowledge of and experience working with IT rules and regulations that apply to financial services is required, 7-10 years’ experience is preferred
• Experience in data management, data operations or data engineering is required
• Excellent ability using SharePoint, Access, and SQL is required
• Problem solver with demonstrated ability to partner effectively with others in handling issues
• Robust project management skills, highly organized with strong attention to detail
• Able to work independently in a fast paced and dynamic environment, handle multiple tasks, consistently meet established deadlines, and deliver exceptional results
• Advanced analytical, investigative and problem-solving skills
• Provide analytical support on internal projects
• Identifying the correct analytical methodologies and techniques required for each spec
• Liaise with internal and external stakeholders to source and extract relevant data sets
• Lead data cleansing and analysis
• Produce tangible visualisations and reports to present back using your knowledge to provide recommendations
• Champion the data library
• Experience within Financial Services is highly favourable
• Assist director in planning, development and execution of ACL Desktop / AX Server and Tableau based data analysis procedures
• Consult with teams to provide data analysis support and guidance during new areas of internal controls support
• Follow development and execution methodologies. Create sustainable and repeatable data analytics leveraging ACL Desktop / AX Server and Tableau platforms
• Act as project lead for automation and support projects. Inform director, wider team, and Senior Management of project status, issues, risks and results
• Display agility and out of box thinking in creating new solutions using existing tools and solutions
• Provide VBA support for excel / access developed solutions
• Demonstrate understanding of Visa's and Internal controls strategic vision, be a self-starter, and be responsible for actions promoting this strategic vision
• Interact with Internal controls team members in working towards departmental goals
• 5-8 years of data analysis experience, leveraging ACL Desktop / AX Server or Tableau tools
• 2-3 years of access / excel VBA macros
• ACL certifications, or Tableau Desktop Certification are highly desirable
• 3-5 years of financial data analysis experience preferred
• Must have a passion for Data, structured or unstructured
• 8+ years of experience working in a technical environment as an engineer or developer
• 5+ years of hands-on experience with data architecture, data modeling, database design and data warehousing
• 5+ years of hands-on experience an ETL tool like Pentaho, DataStage, Informatica, or Ab Initio
• 5+ years of hands-on experience with SQL development and query performance optimization
• 5+ years of hands-on experience with data mining and data analysis
• 5+ years of hands-on experience with unix shell scripting, Perl, and Python. Scala is a plus
• 5+ years of hands-on experience with traditional RDBMS such as Oracle, DB2, MS SQL and/or PostgresSQL
• Strong estimating, planning and time management skills
• Strong understanding of Big Data and open source technologies
• Support internal ad hoc requests related to business and corporate performance through articulating the requirements for and extracting data from various databases within the bank
• Partner with team members, business lines and support groups to develop analytical framework to measure profitability
• Help develop the data analytics roadmap for profitability reporting
• Review of existing profitability reporting in order to support requirements gathering, consistency of design, expectations and project benefits for any process improvement opportunities
• Develops a process by which ad-hoc changes are captured in the process and operating procedure documentation
• Create and maintain well-commented and organized SQL code library for internal reporting and analysis
• Interfaces with the technology teams, and tracks development process
• Performs Hyperion UAT testing, and coordinates the UAT process with the other team members
• Creates and polishes to perfection presentation materials that are used for decision making within Organizational Profitability. Automates generation of materials where appropriate
• Works with LOB partners and modelers on modeling approach, assumption; becomes SME on data and business characteristics for subject portfolios
• Understands Bank’s balance sheet and income statement structure and data, and writes detailed technical requirements necessary for development of new functionality of the Hyperion cube used for profitability reporting
• Bachelor’s Degree in Finance, Economics, Statistics, Computer Science or Business Administration – Required
• Master’s/Advanced Degree - Preferred
• 5+ years of functional/professional experience in data analytics roles
• Required License(s) or Certifications in CFA- Preferred
• Working knowledge of Hyperion or other business intelligence tools a plus
• Ability to execute on projects and work cross-functionally
• Able to document requirements and processes
• Familiarity with financial modeling
• Banking product level experience preferred
• Ability to understand large volumes of multi-dimensional data, and manipulate it with SQL and VBA
• Ability to quickly process and internalize large volumes of information
• Expert level Excel skills, including
• The Senior Data Analyst on the international business team has the responsibility to drive the development of the vehicle valuation portfolio for the local markets
• Must develop a thorough understanding of Kelley Blue Book's existing product offerings and apply the knowledge, perform data analysis, explore possible data sources to build valuation offerings that make sense in other markets
• Will need to perform extensive data analysis to assess data sources available in the local markets and participate in evaluating market opportunities
• Expected to lead a collaborative effort with statisticians, internal and external stakeholders, software engineers and other groups to create and maintain valuation portfolio that fits in the local markets
• Expected to gain a great understanding of the intricacies that drive the new and used car market, both from a wholesale and retail perspective
• Tracks, analyzes and interprets trends in data in order to provide relevant conclusions and recommendations to management
• Will be required to work mostly regular hours, but may occasionally need to be flexible to accommodate meetings with partners in other time zones
• Moderate overnight travel (up to 25%) by air
• 2-4 years of experience performing advanced quantitative analyses
• Ability to transform large datasets into meaningful insights and tools that can be comprehended by the average car shopper
• Project management experience as well as strong communication and presentation skills
• Bachelor's degree (B. A.) from four-year College or university; or two to four yearsrelated experience and/or training; or equivalent combination of education and experience
• Proficient personal computer skills including electronic mail, record keeping, routine database activity, word processing, spreadsheet, graphics, etc
• Ability to read, analyze, and interpret general business periodicals, professional journals, technical procedures, or governmental regulations. Ability to write reports, business correspondence, and procedure manuals. Ability to effectively present information and respond to questions from groups of managers, clients, customers, and the general public
• Ability to work with mathematical concepts such as probability and statistical inference, and fundamentals of plane and solid geometry and trigonometry. Ability to apply concepts such as fractions, percentages, ratios, and proportions to practical situations
• Ability to define problems, collects data, establishes facts, and draw valid conclusions. Ability to interpret an extensive variety of technical instructions in mathematical or diagram form and deal with several abstract and concrete variables
• Must have good technical business analysis skills
• Must have good SQL skills and time management skills
• Strong communication and writing skills a must
• Understanding of major
• Facilitates high level and detailed requirements analysis and translates business requirements into data needs for BI & data solutions
• Leverage thorough understanding of business and system processes to make recommendations and propose technical/non-technical solutions to meet business requirements
• Work with the architects and development teams to implement data & process flows to capture business needs and system deliverables
• Analyze and document the proposed solution’s impact on existing systems, and propose design or process changes to meet business requirements
• Lead and co-ordinate test planning on data and BI solutions
• Create and maintain data and process flow diagrams to be used as project artifacts or reference for future changes to ensure consistent repeatable processes are implemented
• Lead business meetings through walkthrough of data analysis conclusions, results and end-state process flows to validate or educate stakeholders on recommended solutions. Negotiate and gain buy-in on results
• Perform and document data profiling, using industry standard tools, which will be used to assist in data and reporting solutions. Participate in creating project documentation, including design documents, requirement documents, data dictionaries and data mapping documents
• Bachelor’s degree in related field (Finance, MIS, Business Administration, Computer Science) or two year degree with equivalent experience
• 7+ years of experience supporting data architects/technical teams in a large and complex data environments with experience using PL/SQL and query development tools like Toad, SQL Developer, Oracle or SQL based RDBMS
• Experience working with data in a variety of formats including mainframe and distributed environments
• Strong background translating user & business requirements in to complex technical solutions
• Experience in interviewing business users, collecting and interpreting requirements, explaining solution details to business audience and run meetings
• Working experience with agile or other rapid application development methods
• Demonstrated ability to balance data theory with practical solutions
• Knowledge of and experience applying data modeling techniques and best practices
• Thrives in a dynamic work environment; delivers successfully, exhibits flexibility, and is recognized as being a strong team player
• Manage and design the Customer-specific technical solution throughout the project life cycle and provide on-demand support and assistant to customer requests, issues and questions
• Extract insights and actionable recommendations and Investigate anomalies in Big Data
• Install on site and operate - mostly abroad, in unknown environments, troubleshoot in case needed, initiate creative solutions and develop scripts on customer sites
• Prepare for delivery including integration, configuration, testing
• Incorporate research results into the product line and provide product requirements to Algorithm and Development team
• Write analysis reports for internal and external consumption
• Train the customers on the system - system usage and monitoring aspects
• 3 years of professional experience in data analytics with strong data mining and forensic skills
• Strong experience and knowledge at least one scripting languages: Python/Ruby/Perl/java script etc
• Hands-on experience using BI and statistical analysis tools such as SQL, SAS, R, Matlab etc
• Knowledge of Linux, VMs, Cloud
• International Experience working with customers and partners on site
• Ability to execute multiple projects and drive key business results under tight deadlines
• Ability to quickly understand business problems, find patterns and insights within structured and unstructured data
• 5-9 yrs. of data analytics work in a professional environment
• 2+ years of SQL coding experience
• Familiarity with reports generation
• BS degree in a related field is required
• Ability to obtain/or current US government security clearance is required
• Excellent MS Word, Excel, and PowerPoint skills
• Ability to manage stakeholders and meet tight deadlines
• PMP is a plus but not required
• SSIS and SSRS are a plus but not required
• You will be involved in Designing and producing reports to meet client business requirements
• Will be involved in gathering client business requirements , will be predominantly working on Digital Marketing Analytics projects
• Will be involved in creating reports in SAP Business Objects and will need to work on SQL. you will also be involved in statistical modeling using SAS/SPSS/R
• Responsible for reviewing, validating, and entering client processing configurations into various database systems in preparation for client installations, changes, or upgrades on the Star Processing and First Data Debit platforms. Ensures that all data entry work is properly screened for completeness and accuracy prior to entry
• Ensures that work is successfully promoted into production systems on schedule and with the highest level of quality
• . Works with requesting groups to identify and resolve problems with database entries and client configurations targeted for implementation
• Interact with stakeholders to identify critical questions that need to be answered in order for the Analytics team to provide effective KPI’s, actionable insights, and impactful reports that drive critical decision making
• Conduct analysis of data to draw insights that uncover subscriber patterns, user consumption, and related behaviors
• Analyze data to identify outliers, missing, incomplete, or invalid data
• Ensure accuracy of data from source to final deliverable by creating automated quality checks
• Assist in the coordination of data collection from sources which may include contacting various groups outside the company to resolve questions, inconsistencies, or obtain missing data
• Assist in the development of report automation, KPIs, and dashboards
• Create, automate, and maintain reports and visualizations (e.g., behavioral trends and viewership patterns across customer segments, consumption of VOD and live stream, and digital media attribution)
• Work as a client contact for Analytics team, partnering with various departments to identify priority dashboards and reports
• A passion for answering challenging questions and telling stories with data and visualizations
• Self-motivated, detail-oriented, and driven to continuously improve analytics skill set
• PostgreSQL or related querying languages; knowledge of AWS Redshift a plus
• Python or other general purpose programming languages
• Google Analytics/ Big Query or other web analytics tools
• Tableau or other BI-visualization tools
• Proficient Excel skills
• Highly organized and detail oriented
• Team-oriented, but also able to work well independently
• Able to multitask effectively and work well under tight deadlines
• Degree in Mathematics, Statistics, Economics, Actuarial Science, or a related quantitative discipline preferred
• Project & Knowledge management
• You will analyze your stakeholder’s needs. You are able to listen, bring a message across clearly, retrieve the needed information and you have the ability to adapt to the stakeholder’s audience
• You are able to combine your stakeholder’s request with external information and conduct research together with the team
• You are able to interpret the data you've gathered, identify trends and organize and present data in a meaningful way
• You coordinate advanced statistical modeling and data quality projects
• Analysis, reporting and advice
• You analyze the need for information and data to monitor and quantify business & HR objectives
• You have the abililty to interpret large volumes of data in order to draw conclusions using a wide variety of statistical and machine learning techniques
• You support ‘cases for change’ in the HR domain with relevant management information and metrics
• You have a proven track record in coordinating and executing advanced analyses
• You have a degree in Econometrics, Mathematics, Business, Social sciences or related
• You have at least five years of relevant work experience
• You have experience in applied statistical modelling using applications like R, Python, SPSS, SAS and you have proficient Excel skills
• You preferably have experience in the field of IT/Computer Science, programming in SQL and Java
• You have strong English verbal and written communication skills
• You have excellent communication skills and are able to craft your findings and recommendations into the business language of your stakeholders
• You are a great team player, able to actively engage your colleagues by sharing, helping and asking for help
• You have the eagerness and capacity to quickly learn new domains and technologies and apply your skills to unsolved challenges
• You have the ability to navigate a complex international environment
• Manage the Data Warehouse, working with DBAs to achieve and maintain high availability and high performance of the Data Warehouse
• Implement new business requirements, such as enabling new solutions, providing clients with new reports
• Develop complex queries and set up extractions on behalf of the business
• Implement controls to test data quality and ensure full consistency with other LOIM systems and databases
• Support users and troubleshoot data-related issues
• Degree in information technology
• Minimum of 5 years’ experience in a similar role
• Minimum of 5 years’ exposure to the Asset Management or Hedge Fund industry
• Expert knowledge of complex financial instruments
• Expert knowledge of SQL, SQL Server and Data warehouse technologies
• Knowledge of Big Data and related technologies
• Excellent verbal and written communication skills in order to interact with the business
• Fluency in English. French a plus
• Extract, transform and load relevant data and data files from various applications and databases
• Evaluate the appropriateness of data sources for quality and accuracy
• Perform or consult audit teams on data validation, consolidation and cleansing processes
• Perform data analytics procedures to evaluate controls and business objectives. Analytics should be designed to identify outliers, anomalies, patterns, or other compliance indicators that may be hidden in the data
• Develop data delivery processes for both structured and unstructured data types utilizing various internal and external data sources; interface with data experts & data sourcing resources
• Develop detailed business and system knowledge within supported areas. Document business, system, and data knowledge to help build a robust knowledge-base for future efforts
• Train and support audit teams in the analysis of captured data as well as technical training to auditors across all levels
• Automate processes to increase turnaround time on data availability and increase efficiencies in the audit process
• Build & maintain effective working relationships with IS and IT teams across the organization
• A Masters degree is beneficial
• Intermediate knowledge of SQL including: queries, stored procedures and indexing
• 3-5 years + of experience in a customer facing role and/or as a project manager
• Bachelor's degree with a concentration in Information Systems, Computer Science, Computer Engineering or equivalent technical discipline, or a total of at least 9 years of experience in Information Systems and or Data Analysis and Reporting
• 5+ years of Information Systems experience with report writing, reporting applications, and resource management
• Advanced skills in creating complex SQL queries
• Experience developing reports using reporting tools such as Tableau, COGNOS, OBIEE, etc
• Proven ability to provide both detail information and also summarize to a management level
• History of working through management requests in order to determine the data required and delivering on that data
• Experience writing shell scripts
• Experience navigating relational databases of at least 3 terabytes in size
• Intermediate interpersonal, communication, and organizational skills
• Demonstrable ability to work independently
• Auditing - Ensures that tracking meets established standards but will escalate for resolve as appropriate
• Autonomy - Work independently to accomplish tasks within scope of job that lead to outputs of others. Escalates complex issues to and makes recommendations to Senior Manager
• Decision Making - Make relatively moderate-complexity decisions in responding to inquiries and in implementing process improvements. Make decisions in line with organizational policy, or recommends alternatives regarding facilities related queries. When relevant established processes or procedures do not exist, the incumbent shall escalate to a senior manager for a resolution or offer their recommendations
• Monitoring - The incumbent has the authority to collect or be provided with the required information to enable tracking to be done but escalates for resolution if required
• Advisory- Provide advice or suggest how to follow standard processes while recommending and implementing process improvements. Provide resolution on all general administrative or operational matters of a non-controversial nature. Recommend appropriate content for communications, reports and presentations
• Interact regularly with senior managers, and with cross-functional business units to collect information, and to accomplish tasks, as a critical function. Develops relationships to achieve outcomes and to improve cross-group relationships
• Interact with colleagues and clients across a large-size demanding business group. Works with support departments
• Ability to identify the importance of issues and projects and to manage and prioritize multiple tasks
• Ability to work under pressure and meet deadlines in a highly challenging environment
• Self-starter with the ability to work independently under minimal supervision
• Exceptionally strong organizational skills and attention to detail
• Excellent follow-up and problem solving skills
• Ability to make intuitive decisions and prioritize work
• Superior interpersonal and communication (written and verbal) skills
• Advanced knowledge of Access, Word, Excel, PowerPoint and Microsoft Outlook
• Advanced knowledge of SQL, Visual Studio, C#/Visual Basic ,ASP.net, web development
• Knowledge of Crystal Reports desired
• Solid organizational skills required to coordinate and lead a variety of initiatives
• Seasoned broad business knowledge and specific understanding of the organizational unit, its functions and products and customer groups
• Very good understanding of the processes, policies and procedures required for supporting the business
• Professional, polished and discreet
• Undergraduate degree in; information management or software development
• Experienced in working with databases and information/data collection and organization
• Perform analytical programming utilizing a variety of data tools (SQL, SAS, SSIS) from multiple sources including very large data warehouses, data marts, and ad hoc data sources to support existing Medicare programs
• Create financial billing reports and provide analysis using SQL
• Team subject matter expert for all data sources used in analysis and reporting
• Provide in depth analysis to identify root causes and to drive remediation of underlying issues
• Communicate technical information clearly and articulately to a wide variety of audiences (executive management, clients, account managers, etc)
• Take ownership of issues and follow through on all responsibilities
• Work closely with stakeholders on process improvements, ensuring long - term sustainability of processes
• Document and keep all SOPs up to date
• 3+ years strong SQL experience
• 2+ years analysis experience in a business or data analyst type role
• 2+ years of gathering data from Business and Communicate technical information clearly and articulately to a wide variety of audiences (executive management, clients, account managers, etc.)
• 1+ year of SAS experience
• Computer Science or related Bachelor’s degree
• Previous healthcare, finance, or billing experience
• Passion for learning and working with new technologies
• This position will be responsible for collecting, researching and analyzing data related to cost of care and utilization and publish management reports identifying trends and opportunities for cost management and reduction, including the identification of individual provider practice profiles
• Conduct data mining and statistical analysis using the Dental Data Warehouse
• Construct predictive cost of care and utilization models
• Use statistical and analytical methods to identify utilization trends and dentist practice patterns and integrate clinical, third party, Facets claims and UR vendor data
• Investigate utilization problems and collect additional information to close gaps
• Create and publish periodic management reports at corporate, Line of Business, Group, Provider and Member levels as required
• Identify opportunities, through analysis, to manage and control cost of care
• Create and maintain databases as required to support analytics
• Identify providers with abusive claims patterns using analytic and statistical methods
• Create audit databases for investigating abusive providers
• Work cross-functionally and coordinate with others to gather information and overcome challenges in obtaining needed information
• BS/BA in business or related field
• 3+ years of experience extracting data in SQL/Oracle environment with advanced analytical skills using SAS, SQL and/or similar tools
• Advanced analytic skills using SAS, SQL and/or similar tools
• Strong Internet and Microsoft Excel, Word, Outlook and PowerPoint skills with the ability to navigate a Windows environment. Must be able to create, edit, save and send documents utilizing Microsoft Word
• Experience working with data warehouses and databases
• Advanced expertise in statistics including regression modeling
• 3+ years of healthcare experience, preferably in dental insurance/claims processing
• Ability to navigate Microsoft Access Databases and VBA
• Work with clinical and business owners to develop and test new healthcare measures in quality, efficiency and other areas of healthcare measurement
• Transfer knowledge based on research to Systems Analysts, Business Analysts, Developers and others
• User acceptance testing of requirements based on research items
• Research and analysis based on requests from multiple sources
• Research and analyze possible defects in production code
• 3+ years of data analysis experience
• 3+ years of experience writing advanced SQL queries, including proficiency with use of ALL of the following: nested queries, group by clauses and having clauses
• 2+ years of experience with one or more of the following: data manipulation, data profiling or data validation
• 2+ years of experience translating business requirements into technical requirements
• Bachelor’s degree or equivalent professional experience
• Healthcare data knowledge
• Ability to deliver quality work, delivered on a tight schedule, and across multiple concurrent assignments
• Experience validating requirements with stakeholders and the project team, as well as providing suggestions and recommendations
• Experience leading internal review sessions with all levels, including senior leadership
• UAT or other testing experience
• Experience presenting written and verbal data analysis findings, to both the project team and business stakeholders
• Experience with Big Data technology (Hadoop, Hive, Pig, MapR, etc.)
• Experience working with statistics, including experience with SAS or other statistical applications
• Experience with data migration using SSIS or other comparable tool
• Data analyst role responsible for working in conjunction with business analysts to develop, test and implement new production audit opportunities and trends
• Create algorithms to data mine member, claims and COB data
• Support SAS processes in a production environment
• Focus on driving productivity and quality to aide business partners in achieving and exceeding monthly goals
• Analyze a client's data files for quality, quantity, and accuracy
• Use metrics, excellent time management skills and leadership skills to ensure business objectives and goals are met
• Organize and execute multiple re-occurring and one-off tasks and projects at one time
• 3+ years of experience in Analytical role using SAS programming experience
• 2+ years of RDBMS such as MySQL, Oracle, or MS SQL Server
• Understanding of the basic Unix commands, language, utilities and scripting
• 1+ years of experience with SAS Macros
• Experience automating SAS processes
• Experience using FTP/SFTP software
• Experience using version control software
• Experience with healthcare member or claims data
• Coordination of Benefits (COB) experience
• SAS EG programming experience
• Assist in the design and methodology of performance improvement and/or research efforts
• Gather data and evaluate accuracy
• Design and create data collection tools
• Analyze data and develop reports regarding performance at individual and area/department levels
• Proficient with MS Office (Outlook, Word, Excel, PowerPoint, and Access)
• Design, develop, test, and implement basic relational databases
• Assist in the maintenance of existing databases as needed
• Director in advance to any barrier(s) to meeting deadline(s)
• Coordinate with employees assisting in data collection
• Collaborate with medical, counseling, case management, and administrative staff to ensure reports are accurate and meaningful
• Generate reports from a variety of internal and external data sources
• Be familiar with, and have the ability to, format data in various ways
• Create and/or maintain documentation and products in a shared network space
• Analyze data for trends, improvements, and areas of concern
• Assist in the preparation of publications and presentations
• Coordinate with other members of the department to provide back up for various projects
• Participate in committees as assigned
• Able to present data in tabular and graphic formats
• Proficient with basic, descriptive statistics
• Provide analytical measurement on quality, performance, and research initiatives, as assigned
• Compile, organize, and analyze data from multiple sources
• Assist in maintaining a work environment free from recognized hazards that create a risk of injury to employees, patients or visitors and that all accidents and incidents are reported by employees and properly investigated. When appropriate, assist with the return of all workers with work related injuries and illnesses to gainful employment
• Participate in professional development
• Provides statistical and analytical support in effort to achieve CMMI Maturity Level 5
• Gathers, analyzes, and interprets a wide variety of data in order to develop and refine process performance models and baselines
• Measures process stability and accuracy
• Analyzes existing processes, proposes improvements, and develops and enacts deployment plans. Utilizes quantitative methods to evaluate the effectiveness of those improvements
• Develops and implements programs to ensure products and services meet company standards and internal customer requirements
• Identifies new ways to utilize data and statistical methods to improve business processes throughout the organization
• Develops and conducts training to encourage use of statistics and other mathematical techniques throughout the organization
• Maintains current knowledge of relevant technologies and subject areas
• May provide guidance and work leadership to other team members
• 5-8 years of related experience
• Understanding of the CMMI Institute Capability Maturity Model Integration (CMMI) and ISO 9001 requirements
• Six Sigma Black Belt certification
• Ability to perform statistical analyses and interpret the results
• Experience in statistical modeling for software development projects seeking CMMI ML 5 is desired
• Experience in statistical modeling: linear regression is required; nonlinear regression modeling is desired
• Experience in hypothesis testing: parametric is required; nonparametric is desired
• Experience with statistical software (R, Minitab, JMP, etc.)
• VBA coding experience is highly desired
• Experience working in a software development environment
• Experience working in an Agile software development environment is desirable
• Advanced knowledge of the principles, methods, and procedures related to process improvement
• Comprehensive knowledge of the work processes, methods, and techniques of software development
• Excellent oral and written communication skills at all organizational levels
• Experience and proficiency with Microsoft Office products (Word, Excel, Outlook) is required; experience in Project and Visio is desired
• Creative problem solving ability
• Highly analytical and accurate
• Ability to learn and adapt
• Ability to work independently and in teams
• Executing Data Analytics - Create/enhance analytical procedures, create data dissemination mechanisms/procedures which summarize data in an easy to understand display, create/maintain customized SAS stored processes
• SAS Macro libraries and JMP scripts, perform risk analysis, respond to complex data requests that require data mining, extraction and query optimization services, investigate and recommend new analytic technologies and advanced
• Bachelor's degree in Econometrics, Finance, Statistics, Math, Economics or related degree (High School Diploma and 4 additional years of experience may be substituted in lieu of degree)
• Ten (10) years of relevant experience (a Masters or CFA may substitute for 2 years of experience)
• Minimum of five (5) years hands-on data analytics
• Proficient in statistical and data analyses
• Knowledgeable of fundamental factor models such as macroeconomic factor models, cross sectional fundamental factor models and time-series fundamental factor models
• Familiar with financial data and the basics of the financial services industry, including derivatives (futures, options and swaps) and financial reporting
• Hands-on experience with at least one or more of the following: SSMS, SSRS, JMP, MATLAB, Revolution Analytics "R", Greenplum, PowerPivot, Stata, SSAS, SPDS and SharePoint
• Advanced ability to compose materials such as detailed reports, work‐related manuals, publications, etc
• Demonstrated ability to communicate with different levels of employees (managers, supervisors and team members) are a must
• Ability to obtain NACI clearance (US Citizenship or Permanent Residence status required)
• Proficient with the SAS EBI Platform - extremely beneficial
• Degree preferred
• Proficiency in statistical and data analyses using SAS is preferred
• The Data Ops Analyst role resides within the Ford GDIA organization which was formed to support the client’s Data Acquisition strategy
• You will be responsible for providing the data support for enterprise data integration tasks, including ingestion, standardization, enrichment, mastering and assembly of data products for downstream applications
• Work on all the data types across the enterprise including Customer, Dealer, Vehicle, Manufacturing, etc
• Implement an Enterprise Data Governance model and actively promote the concept of data sharing, data reuse, data quality and data standards
• Bachelor’s Degree in Computer Science or related field from an accredited college or university
• Minimum of 2 years¿ of experience in Big Data / NoSQL technologies including Greenplum & Hadoop (HDFS, MapReduce, Hive, Shark, Spark, etc.), especially command line experience with loading and manipulating files within HDFS
• Ability to work in different database technologies including Big Data / Hadoop (HDFS, MapReduce, Hive, Shark, Spark, etc.), RDBMS and NoSQL
• Knowledge of data transfer and ingestion technologies including Attunity
• Ability to write complex SQL queries needed to query & analyze data
• Ability to quickly comprehend the functions and capabilities of new technologies
• Strong team player, with the ability to collaborate well with others
• Strong analytical and problem solving skills,
• Resourceful and quick learner ¿ Highly self-motivated
• Superior organization, coaching and interpersonal skills
• Strategic and clear thinking to translate discreet and complex ideas to business-driven results
• Bachelor’s degree from accredited university
• Act as an internal consultant supporting our global customer and dealer, Marketing, Sales and Service business unit data strategy
• Work closely with data scientists and data analysts to better understand and evaluate data requirements and the type of data needed
• Provide visibility to data quality issues and work with the business owners to fix the issues
• Enable tactical and strategic data standardization transformations for data visualization
• Evaluate, explore and select the appropriate data platform technologies including Big Data, RDBMS & NoSQL to meet the analytics requirements
• Implement enterprise data governance model and actively promote the concept of data sharing, data reuse, data quality and data standards
• Build the metadata model & business glossary by gathering information from multiple sources: business users, existing data sources, databases and other relevant documents and systems
• Strong problem formulation, analytical and problem solving skills, with the ability to communicate in a clear and succinct manner
• Strong interpersonal, and leadership skills, with proven abilities to communicate and present complex topics to leaders and peers in a simple, clear manner
• Self-starter that is detail-oriented with the ability to multi-task and work independently
• Effectively collaborate with others and possess excellent oral/written communications in English
• Strong team player, with the ability to collaborate well with others, solve problems and actively incorporate input from various sources and team members
• Ability to anticipate obstacles, effectively evaluate information, and develop plans to resolve them
• Change oriented, with the ability to actively generate process improvements, support and drive change, and confront difficult circumstances in creative ways
• Resourceful and quick learner, with the ability to efficiently seek out, learn, and apply new areas of expertise as needed ¿ Superior organization, coaching and interpersonal skills, combined with effective leadership, and decision-making
• 5+ years of experience working with big data-related projects, and data operations experience compiling data for analytics, working with data analysis methodologies and supporting tools
• 2+ years of experience in Big Data, RDBMS, NoSQL technologies including Hadoop, SAS, MapReduce, Hive, Shark, Spark, QlikVew, etc
• Knowledge of command line experience with loading and manipulating files within HDFS
• Experience with data transfer and ingestion technologies including Attunity
• Ability to write SQL queries needed to query & analyze data
• Bachelor’s degree in Mathematics, Statistics, Computer Science or academic equivalent from an accredited college or university
• Compiling, processing and analysing data with MS Excel, MS Access, SQL and other tools
• Data modelling using Fortna’s proprietary tools and other specialised systems for financial and operational modelling
• Writing and delivering high quality analysis of data evaluation
• Develop new templates and calculators that will support our company different practices, this includes leading the research and look for the resources needed
• Bachelor’s degree in Math, Economics, Logistics, Supply Chain, or Business
• 2+ years of data analysis experience; previous experience performing SQL data analysis is preferred
• Excellent analytical and research skills
• Intermediate to Advance user of MS Excel, Access and SQL
• Strong organization, document writing, and communication skills
• Ability to work under deadlines in support of multiple projects throughout various countries
• Ability to develop structured problem solving skills
• Act as a liaison between the business customer and IT to identify business processes, system and product requirements
• Coordinate Mass Updates, Re-organizations, Acquisitions, and Divestitures that have an impact on PeopleSoft data
• Analyze and troubleshoot data in PeopleSoft, especially when there are issues with PeopleSoft data
• Do non-standard PeopleSoft data entry where subject matter expertise is required
• Recommend process improvement where processes are broken
• Responsible for reviewing possibilities to standardize and transition data entry activities to groups outside of subject matter experts
• Perform testing for any changes in PeopleSoft as part of enhancements and/or projects
• Maintain and apply a strong knowledge of the customer’s business and regional/global processes to develop solutions
• Coordinate enhancements for Smart Forms by collecting requirements from the business
• Create and/or deliver HR and client communications regarding PeopleSoft data changes and/or Smart Forms
• Conduct training on PeopleSoft and Smart Forms to HR customers
• Conduct in depth analysis to determine responsive and profitable customer segments
• Develop and execute experimental designs and optimization schemes for ongoing marketing campaigns to improve marketing effectiveness and ROI
• Develop and continually improve customer segmentation, targeting propensity models (response, attrition models), and customer lifetime value model using advanced statistical techniques
• Translate analysis results and modeling outcome into understandable and actionable business knowledge; effectively and clearly presents findings to non-technical audience
• Must be able to interact productively with key organizational decision makers
• Collaborate closely with other analytic teams across the organization to share findings and best practices
• Develop a strong partnership with the BI Team in performing complex data extractions, manipulations and validation to ensure accuracy and appropriateness of analytic model
• Bachelor degree in Statistics, Economics, Operations Research, Applied Math, Computer Science or related quantitative field. Graduate degree preferred
• 3+ years of experience in the Analytics field
• Advanced SQL programming skills and experience working with large and complex databases, preferably in a marketing capacity
• Knowledgeable and experienced with analytic methodology, statistical analysis and test design including experimental design, A/B testing, sample size, and t-tests
• Predictive modeling skills using statistical programming tools (SAS, R)
• Proficient with Microsoft Office products (Excel, PowerPoint, and Word)
• Experience with Business Intelligence tools (Tableau, Cognos) a plus
• Analytical thinker and a team player who thrives in a fast paced environment
• Understand how the Service team utilizes various applications in order to provide analytical reporting and applications to process owners and leaders
• Combine and consolidate datasets from various sources to produce meaningful reporting of the "big picture"
• Drive requirements gathering, development and testing of new tools and reports
• Work with management and peers to create and run as needed reports on multiple company databases
• Check for validity of collected data using several techniques, including, but not limited to, on-line comparison tools, MS SQL server, data editing/tabulation software
• Assist with web development for new or enhanced tools and reporting
• Manage project lifecycle independently while ensuring timely implementation. Act as liaison between business and IT
• Assist with other Commercial support as needed
• Requires a Bachelor's degree
• Must be able to effectively communicate, particularly through written communication
• Meticulous attention to detail and accuracy
• Advanced knowledge/use of Microsoft Access, Excel, PowerPoint, and MS SQL server
• Knowledge/use of OBI, Business Objects or similar business analytics application
• HTML skills, preferred experience using Script Case and Word Press
• Knowledge/use of Oracle or similar ERP application
• Experience with Salesforce.com or similar CRM application
• Knowledge/use of Sharepoint
• Playing a lead role in software design, architecture, requirements analysis, investigation of new technologies, and software development
• Collaborate as a member of an agile team to get products developed and completed with best in class software development
• Working closely with business and IT teams to define the end to end solution for large scale data and analytics solutions
• Lead analysis, design and development of enterprise data and analytics use cases and their solutions
• Mentoring team members on best practices and best use of technologies
• Excellent interpersonal and communication skills and an ability to work effectively with teams
• Strong analytical skills and a demonstrable bias toward action.Development
• Mentor junior staff and help improve overall efficiency of data analysis both technically and procedurally
• Take data stewardship and provision data to multiple customers while adhering to enterprise quality standards
• Develop, maintain and execute sourcing scripts and applications to collect data from a variety of client and public sources
• Develop, maintain and execute tools to aggregate, validate, transform and retrieve data in internal Oakleaf data stores to serve a variety of different modeling and analytical needs
• Analyze and document data processes, and information flow
• Analyze and document data conventions used in outside data sources
• Design logical database models using normalization/ standardization techniques
• Implement and support ad-hoc queries and reports
• Develop strategies and data structures to unify information of various types from numerous disparate data sources and facilitate re-use across clients and usages
• Aggregate and transform time-series data and other large datasets
• Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science, Business, Finance, Accounting or related field
• Domain knowledge of financial instruments and particularly the mortgage lifecycle is highly preferred
• 4+ years of experience in a programming role using Python, R, or other industry standard languages
• 3+ years of database administration experience and querying and creating stored procedures using data querying languages
• Familiarity with basic accounting and statistical topics
• At least 2 years as business analyst. Working in the High-Tech industry – an advantage
• Technical BI skills (ETL’s, BI Tools as developer)
• Experience in developing statistical scripts over databases
• Acquaintance with operations systems (ERP’s, CRM’s) – an advantage
• Reporting to VP IT
• Design, develop, analyze, evaluate, test, debug, document, and implement moderately complex software automation applications from collected specifications/requirements
• Under general direction, devise or modify procedures to solve complex problems while considering equipment capacity, bandwidth, operating time, and form of desired results
• Provide Windows Server administrative support for the production, UAT, and development environments. Participate in occasional evening change windows as required
• Work as a team member in Revenue Assurance providing technical recommendations to solve for business issues
• Responsible for producing high quality deliverables in a timely fashion
• BS in Engineering, Mathematics, CIS or related field, or equivalent relevant experience in required
• 3+ years enterprise experience with software development in an intranet web environment
• 3+ years enterprise experience with VB.NET
• 3+ years enterprise experience with CSharp.NET (C#)
• 3+ years enterprise experience with JavaScript
• 3+ years enterprise experience with JQuery
• 2+ years enterprise experience with MVC
• 3+ years enterprise experience with ANSI SQL
• Competency to work at the highest technical level at all phases of the software development lifecycle
• Ability to accept responsibility for multiple development projects
• Ability to engage and network with contacts inside and outside the team
• Oracle 10 or above
• Windows Server Administration
• IIS 7+ Administration
• Java programming
• Functional analyst within the Internal Reporting and Analytics Solutions design and management team
• Work directly with user community to assist in gathering requirements, prototyping and designing reporting , data analytics and visualization solutions
• Deliver business as usual and maintenance activities for reporting applications as required
• Deliver functional requirements, design specifications, testing scripts and training materials to support EPM/BI capabilities
• Flexibility and collaborative work approach to solve complex problems and to develop customer-specific solutions - taking into account multiple internal and external stakeholder groups
• Compliance to Verizon-wide policies and procedures
• BA/BS degree with concentration in General Accounting, Finance, FP&A, IT, Project Management or equivalent work experience
• 3+ years of directly related experience
• Data Analytics, Oracle EPM and/or BI background
• Proficiency with a Major BI reporting tool
• Strong interpersonal, influencing, communication and organizational skills
• Ability to interface with various/complex stakeholder groups and functions, as well as various levels of management
• Gather and maintain data across Teradata, Hadoop and Aster
• Data extraction, transformation and ETL using SQL Server, Teradata, Hadoop
• Analyze the data using big data tools to identify opportunities to improve the customer experience and drive revenue generation, including Python, R, SQL, HiveQL, C#, R etc…
• Develop models and use cases for engagement and socialization with the business
• Self-starter: Able to work independently and multitask under short deadlines based on general directions
• Candidate needs to have proficiency in creating complex SQL and ETL in variety of databases in priority order: Teradata, SQL Server and Oracle
• Proficient in PL/SQL programming - Stored Procedures, Functions, Packages, SQL tuning, and creation of Objects - Tables, Views, Materialized Views, Triggers, Sequences, Synonyms, etc
• Extensive experience in database and SQL skills such as analyzing and improving table performance Analysis and tuning SQL queries. Experience with performance/scalability tuning, algorithms and computational complexity
• Strong experience with data analytics and high volume data processing. Familiarity with a variety of data formats and protocols of structured and unstructured data
• Has strong skillset in creating reports and performing business analysis in Tableau and Excel Proven ability to analyze data and identify opportunities. Ability to analyze large volume of data and identify patters
• Excellent skills in Python and R
• Strong communication skills to communicate analysis, findings and insights
• BA/BS degree with concentration in general Accounting, Finance, FP&A, IT, Project Management or equivalent work experience
• 4+ years of directly related experience with a management background
• Data analytics background
• Oracle enterprise performance management and business intelligence/ Hyperion
• 6+ years of statistical analysis or data analysis experience; or 3+ years of related IT experience, including data warehouse, coding or ETL experience, or analysis or data analysis experience; or 3+ years of HEDIS data analysis experience including measurement and rates impacted
• Advanced knowledge of Enterprise Reporting and Analysis tools, SQL, and Microsoft Office applications, including Excel and Access
• Encounters experience preferred
• Interface with PM and business customers, gathering requirements and delivering complete reporting solutions
• Execute new analysis from top to bottom within broadly defined parameters
• Modifies, designs, develops, debugs, and supports more complex analysis
• Participate in industry and other professional networks to ensure awareness of industry standards, trends and best practices in order to strengthen organizational and technical knowledge, and
• Develop effective relationships within and among departments and other AGILE team members
• 5+ years’ experience building data warehouse and business intelligence solutions in a SQL Server environment
• 3+ years of SQL Server Reporting Services (SSRS) experience
• Strong T-SQL skills, including 5+ years’ experience building and modifying stored procedures, functions, creating tables and views
• 3+ years Healthcare Industry experience
• Understanding of business requirements in user story (acceptance criteria) format
• Must demonstrate a strong attention to detail
• Deep understanding of relational databases
• Experience with business intelligence software is a plus
• Experience / knowledge with SQL Server Database Administration (DBA) is a plus
• SQL Server Analysis Services (SSAS) experience is a plus; and
• Expertise in understanding and writing SQL
• Demonstrated high competency in balancing multiple projects
• Experience in process analysis and documentation
• Understanding of various issues tracking/resolution, scope estimation, and scope management processes
• Experience with Oracle databases, DataFlux ETL, or Cognos BI tools is preferred
• Experience with IBM Rational Suite tool, including RequisitePro, RSM, ClearQuest, and ClearCase, is preferred
• Education – BS degree preferred
• Experience – 5+ years
• Significant experience writing moderate to complex queries, performing analysis on data and presenting findings
• Experience with SQL and ETL tools
• Experience with analyzing large datasets via Excel, MS Access
• Experience performing data quality reviews and data gap analysis
• Ability to enhance, edit and correct data content issues based on knowledge and experience *
• Experience with standard office software (Word, PowerPoint, MS Project, Visio, etc.), including knowledge of “power user” functionality such as pivot tables, and connection of these tools to external data sources
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Strong skills in problem solving, critical thinking, organization, prioritization, multitasking, and follow-through
• Ability to formulate conclusions and define next steps upon completion of a data quality review process
• Experience with large data sets, indexing to optimize performance, unstructured data and understanding of OCR technologies is preferred
• Experience in project management methodologies
• Experience performing business analysis
• Experience in business and technical requirements gathering and related documentation
• Independent thinking and decision-making abilities
• Excellent organizational skills and interpersonal skills
• Knowledge of application testing and methodologies is preferred
• Experience with Microsoft TFS and sharing tools (SharePoint) is desired
• Excellent verbal and written communication skills, and ability to interface effectively with product, development, data inquiry and data fulfillment teams
• Supports ongoing return activities required for processing non-saleable inventory handled by company third party processor, including monthly process to physically identify items that could not be matched, conduct inventory cycle counts as directed, and physically inspect and/or validate condition of product or shipments
• Manage ABSG business process and reporting tools used to set up, send and monitor inventory and sales data sent to suppliers to ensure proper data governance and compliance with supplier agreements
• Conduct unit variance reconciliation activities needed to resolve unit of measure issues or quantity discrepancies
• Create manual reports as needed for suppliers, quarterly reconciliations and research purposes using ABSG data warehouse environment
• Assist with cost variance research and other reconciliation activities as needed to ensure appropriate credit is issued for product
• Develop and track performance metrics used to monitor operational performance of third party processor and ensure timely disposition of product
• Research and assist with the resolution of data issues identified by suppliers or internal stakeholders
• Support data validation activities as needed for supplier audits
• Assist with the set-up activities of new customers on company sponsored return programs as needed
• Provide support as needed to obtain return authorizations from suppliers, manage handling of debit memo process, or create price files used by customer return programs
• Monitor distribution center compliance as it relates to returns processing standard operating procedures
• Good interpersonal and relationship building skills
• Strong analytical, conceptual and problem solving skills to evaluate business problems and apply knowledge to identify appropriate solutions
• Strong knowledge of healthcare distribution business, product and supplier base, supplier interrelationships and industry trends
• Ability to implement processes resulting in satisfactory audit practices
• Ability to create reports using Crystal Report Writer or Sequel Server reporting tools
• Strong computer skills in order to operate effectively with company systems and programs; knowledge of Microsoft Word, Excel, PowerPoint, Access and Outlook
• Experience in reviewing and managing compliance to contracts
• Bachelor’s degree in Business Administration, Computer Science or relevant discipline
• XML interface analysis and interface field mapping skills
• Relational database design and development (SQL server/Oracle)
• Business analysis experience involving domain knowledge in mortgage origination, secondary market or loan servicing
• Provides direction for assigned components of project work
• Given scope of work, minimal feedback/rework is necessary
• Evaluates effectiveness of actions/programs implemented
• Proactively records workflows, deliverables, and standing operating procedures for projects
• 1-3 years experiences in SAS programming in DATA STEPS, PROCS, and MACRO
• Coordinates team/project activities&schedules
• With some feedback and mentoring, able to developproposals for clients, project. structure, approach & work plan
• Proactively records workflows, deliverables and standing operating procedures for projects
• Independently determines and implements appropriate measurement and analytical methods to achieve specified analytical project or tasks objectives
• Exercises independent professional judgment regarding analysis assumptions and data quality. Identifies and resolves data quality issues, as required
• Coordinates the work of other project team members (UCDA staff, regional analytic staff, and contractors) to accomplish specified analytical project or task objectives
• Determines the most informative approaches to summarizing data and communicating analytical results. Develops, as required, innovative or customized templates and formats
• Implements specified quality assurance procedures to ensure accuracy of project data, results, written reports, and presentation materials
• Designs and creates written reports and presentation materials describing project objectives, methods, data, and results
• Given project or task data requirements, determines the most efficient approach to data collection and validation and works independently to obtain needed data from KP HealthConnect information systems (e.g. Clarity)
• Trains and coaches less-experienced healthcare data analysts on data retrieval techniques, programming practices, and statistical analysis and data visualization methods in the context of specific tasks
• Specifies project quality assurance reviews and tests based on project characteristics and requirements. Provides guidance to other healthcare data analysts regarding the implementation of such QA reviews and tests
• Develops detailed measurement and reporting specifications based on project characteristics and requirements provide by project leadership. Provides guidance to other healthcare data analysts regarding the implementation of such specifications
• Applies analytic knowledge, skills and experience to perform project-related work, complete specific project tasks, and create project deliverables
• Minimum five (5) years of experience in data analysis
• Knowledge of healthcare industry, especially healthcare analytics preferred
• Familiarity with Kaiser Permanente healthcare system preferred
• Management console administration
• Lead Production support activities
• Present solutions to Architectural Board and other program groups
• Act as ETL Lead and manage on and offshore resources
• Lead warranty support and long term maintenance/production support
• Interpret client-supplied business requirements documents (BRDs)
• Translate BRDs to functional specifications
• Work with offshore developers and data architect to design analytical reports and multidimensional data structures to support requirements
• Translate functional requirements into technical requirements
• Design analytical reports to support the requirements based on an existing user interface design
• Assist in the development and unit testing of new reports
• Assist system integration testers, performance testers, and user acceptance testers as needed
• Minimum 3 Years of experience in Cognos report development
• Experience in Oracle SQL
• Experience in Linux or Unix
• Experience in Cognos Administration activities
• Heavy experience in troubleshooting Cognos analytics and code reviews before migration into any environment
• Manage and coordinate Cognos code promotion process
• Administer the code check in/out from code repository
• Use of automated CM tools to implement CM policies and procedures
• Assist to improve and develop the CM process, working methods, and tools
• Manage and track changes to baselines
• Team player and ability to lead a team in a matrix organization model
• Assist the onshore and offshore team in coordinating code promotion
• Configure and manage environment for data profiling and analysis
• Perform data profiling and analysis to clarify the nature and scope of data issues
• Identify and document data-cleansing requirements
• Develop strategies for duplicate identification and merging
• Drive the definition, development, testing and application of data cleansing strategies in a hands-on fashion
• Work with Subject Matter Specialists (SMS) to identify and prioritize data quality issues
• Profile data to determine scope, risk, and cleansing approaches
• Present cleansing options with recommendations for addressing issues
• Develop and test cleansing scripts to automate cleansing wherever possible
• Coordinate cleansing using data verification services where appropriate
• Coordinate the application of cleansing activities with production support staff
• Coordinate data entry resources and tasks and where manual cleansing is required
• SQL fluency required, especially SQL Server
• Experience cleansing consumer data in volume (address, phone, email, etc.)
• Familiarity with profiling tools and data cleansing services is strongly desirable
• Great team player with a positive attitude
• A highly proactive, energetic, and enthusiastic approach, projecting a sense that business is being taken care of responsibly
• Ability to see the “big picture” while addressing critical details
• Problem solving and analysis skills, combined with strong business judgment
• Attention to details, consistency and reliability of performance under tight deadlines
• Superior organization and planning skills. Capable of handling multiple activities and ad-hoc requests simultaneously
• Willingness to adapt to fast-paced delivery cycles; ability to multi-task
• Five + years of professional experience as a data analyst
• Must be able to travel 50%
• Map and analyze multiple data flows across transaction processing, trade settlement, asset servicing, accounting, reference data and portfolio analytics
• Work with Information Architects to ensure proper Logical Data Models are defined correctly, including a data dictionary that can be used to validate attributes and values
• Perform detailed analysis of data in source systems against what is being delivered to clients today, followed by comparison against Logical Data Models
• Orchestrate with Chief Data Science group to perform data profiling to find outliers and exceptions
• Validate all data attributes and values with Operations or appropriate data owners
• Produce requirements documents for upstream systems to build new feeds that provide high quality data
• Collaborate with application development team to build data quality testing rules into the new platform, ensuring that all data received from upstream systems adheres to quality standards
• Minimum 6 years experience as a data and/or business analyst in the financial services industry
• Ability to analyze complex cross functional business processes and define integrated requirements
• Can ensure the end to end solution will deliver the required business results
• Communicates with business SMEs to ensure expectations are kept in line with project status
• Creates/revises/executes the following deliverables using industry standard techniques as necessary, including but not limited to: process maps, data flow diagrams, requirements specifications, functional specifications, use case scenarios, acceptance testing
• Define, design, develop and maintain interactive data visualizations via Tableau
• Use SQL to pull data from different backend systems
• Work with development and operational teams to understand and document their reporting and analytical needs
• Mine and structure data to provide hidden insights into data collection and algorithm performance
• This position is for a Data Analyst/System Design Analyst to support a large global program
• Ideal candidate must have strong data analytics skills and 5+ years of large project design and development
• 5+ years of project design and development experience on large projects
• Experience with solution delivery methodologies and a strong understanding of design and development specifications
• Project development skills with development tools such as Java, Hadoop, Mainframe, and/or SQLServer
• Analytics experience
• Marketing and Sales business knowledge
• Computer Science
• 8+ years of progressive data analysis experience or any equivalent combination of education and experience
• 2+ years designing and executing SQL queries
• 2+ years using a statistical programming language such as R, NumPy/SciPy/matplotlib or equivalent
• 2+ years extracting and parsing unstructured data
• Familiarity with Web site/application performance optimization techniques, streaming media technologies, and Web/DDoS attack vectors
• Excellent English writing and communication skills
• Highly inquisitive and able to combine smaller independent pieces of information to create a larger, more coherent picture
• Ability to deal with a demanding and varied workload and to switch priorities at short notice
• Responsible for the aggregation, analysis, interpretation and reporting of customer and sales data on a regular basis
• Offer insights and new methodologies for reporting where opportunities exist
• Tackle complex business problems by converting raw complex data sets into meaningful and actionable business ideas through statistical analysis
• Communicate data insights or outcome to business intelligence and management teams
• Track key metrics and trends of all business intelligence-related data for our all sites and channels, such as the number of traffic, sales, cost, revenue, airlines, season by creating insightful automated dashboards, visualizations reports
• Build and automate actionable models and reporting for key business processes
• Identify relationships and trends in data, as well as any factors that could affect the results of our information
• Work closely with the business and technology leaders and managers to understand the organization’s data structures and content, to lead the design and execution of audit’s data analytics to achieve efficiencies and increase effectiveness of the overall audit activities
• Leverage and develop subject matter expertise in the knowledge of the company’s data environment, the ability to access data, the use of analytical tools, and the application of an effective methodology
• Experience in collecting and analyzing complex data, evaluating information and drawing logical conclusions
• Proficient in Adobe Analytics, Excel, SQL and Business Intelligence tools such as MS-SQL, Tableau and Kibana
• Ability to excel and manage in fast-paced atmosphere
• Determined, strong work ethic, positive attitude, team player, resourceful, detail-oriented
• Expertise with detail-oriented work
• 5-7 years of relevant industry experience in analytics
• Advanced SQL querying skills
• Experience using Tableau and/or other BI tools
• Experience working with large quantities of raw, disorganized data
• Highly analytical mindset--you’re critical, quantitative, inquisitive and insightful
• Entrepreneurial in nature--you’re resourceful, adaptable, and have an eye for optimization
• Active Eventbrite user with a passion for live events
• Manipulate and analyze complex, high-volume, high-dimensionality data from varying sources using a variety of tools and data analysis techniques
• Define, track and report key metrics to assess overall business health
• Ongoing analyses to assess subscription health and provide strategic input to stakeholders
• Connect findings and recommendations to business initiatives and collaborate with key stakeholders at various management levels
• Collaborate with world-class game developers across a variety of disciplines (engineering, game design, live operations, UI/UX, and community) to form and test theories on player behavior
• Work closely with engineers to understand and efficiently leverage game databases (MySQL)
• Find answers to business questions via hands-on exploration of data sets via SQL, dashboards, statistical analysis, and data visualizations
• Prepare and present weekly reviews on the game’s performance
• Create and manage multiple A/B tests to gain valuable insights on KPIs including retention, acquisition, and monetization
• Measure the success of product features after release and optimize their performance through rapid, data-driven iteration
• Play with an amazing dataset
• Collect, consolidate and validate operating, financial and market data
• Develop, use and maintain tools for handling, analysis and validation of data
• Performs executive level business analysis and creates presentations explaining financial performance for the entire value chain
• Support the forecasting and budgeting processes for short term and long term business planning. Provides insight and support to functional leadership in development of strategic plans
• Maintains a working knowledge of cross-functional performance drivers. Researches new business developments and ensures that business plans accurately reflect the current environment
• Works with complex, unstructured data residing in multiple systems to develop a comprehensive view of the business
• Performs ad-hoc analysis in support of strategic initiatives
• Minimum 5 years of financial or business analysis experience required
• Extensive data modeling experience required
• Advanced Excel proficiency
• Ability to meet time sensitive deadlines and requirements
• BW/BI, SAP experience preferred
• Develop deep understanding of strategic packaging components to support development of new packaging programs and contribute to troubleshooting and problem solving
• Lead program of work to capture and maintain packaging data and integrate it into global sustainability database
• Develop reporting score carding system for sustainable packaging performance
• Maintain global program for the management and reduction of packaging fees in key markets
• Support the integration of sustainable packaging requirements into innovation processes, including Stage Gate
• Support execution of packaging optimization programs to deliver against PepsiCo's Sustainability and Innovation agenda
• Provide cross functional project leadership across Global R and D, Operations, Procurement, Global Sustainability, PepsiCo Design Function, Consumer Insights, Sales, Marketing, Legal, and Supply Chain
• Build strong relationships with internal and external partners
• 5+ years' experience in data management and analytics, programming and/or IT with specific experience in managing information and reporting in a commercial environment
• Packaging experience/exposure preferred
• Understanding of procurement/supply chain processes and responsibilities preferred
• Highly motivated individual with a passion for sustainability
• Clear and analytical thinker with the ability to identify process improvement opportunities and visualize "white space" data management and reporting solutions given specific functional requirements
• Ability to quickly learn (execute and troubleshoot) new software/programs
• Highly proficient in Excel, including use of advanced functions and programming in Visual Basic. Experience with additional reporting tools (e.g. Tableau, Business Objects) is preferred
• Strong time management skills - ability to handle multiple projects, set priorities and plan
• Very strong communication (spoken and written) skills, which includes the ability to
• Translate "big data" into meaningful and structured reports relevant to the intended audience (e.g. Sr. Leadership vs an individual farmer)
• Interpret and consolidate feedback on the SFI Code and Questionnaire into well-written, concise and intent-based enhancements
• Switch between layman's and IT vernacular as needed
• Lead MFC evolution for Business Analytics to deliver actionable insights to the business
• Acquire business process/functional and data knowledge of new customer business domain
• Support option evaluation and impact analysis for new technologies and capabilities
• 2+ years of hands on experience implementing complex predictive models and technical solutions using broad range of technologies
• Knowledge of statistical analysis concepts and tools such as SAS and R
• Experience using Big Data tools such as SAP HANA, Hadoop, or Netezza
• Strong knowledge of SQL and SSIS
• Strong executive communication and documentation skills
• Must have ability to quickly ramp up on new technologies and tools
• Knowledge of functional data for financial operations
• Ability to handle multiple concurrent activities
• Strong team player with commitment to excellence
• Ability to mentor junior team members on the technology development standards
• Ability to lead requirement solicitation sessions
• Proficiency in Tableau data visualization is highly preferred
• Assist director in planning, development and execution of Tableau based data analysis procedures and VBA based solutions
• Provide functional and technical support for Oracle R12
• Provide support to the existing data analytics environment, including periodic data refresh, troubleshoot errors, fix bugs, and implement enhancements
• 3-5 years of data analysis experience, leveraging Tableau or other visualization tools
• 4-6 years of access / excel VBA macros and VBA programming
• 2-3 years of Oracle financial package knowledge
• ACL knowledge a plus
• Supports the utilization of sound study design process when assisting in the development of performance improvement, quality, patient safety and research methodologies
• Evaluates the effect of performance improvement initiatives on clinical, efficiency and effectiveness, genuine caring and service outcomes by identifying and compiling data from multiple sources and databases to produce comprehensive reports
• Supports Patient Satisfaction sampling measures, assists in the analysis of reports and provides assistance with education to recipients of data regarding findings
• Identifies, assesses and designs appropriate tools, database queries and reports for collection of demographic, clinical and quality data
• Participates, when appropriate, in team meetings with providers, clinical and office staff to ensure data integrity and facilitate data analysis and synthesis
• Identifies issues with data collection methods and determines need for changes in data collection and management processes
• Works with management, providers and practice managers and supervisors to develop report cards and/or dashboards as appropriate to ongoing measurement and improvement initiatives
• Assures methods for evaluation of Processes or Performance Improvement initiatives meet/exceed accreditation, regulatory, and institutional standards
• Provides ad hoc reports as directed
• Maintains competency in Statistical syntax programming application, CCS, HIS, Midas +, Power Chart, Centricity, Access, Word, EXCEL, Powerpoint and other applications specific to duties
• Advances knowledge of current computer software and demonstrates ability to learn and utilize new technology, concepts and software applications and assimilate them into daily work routine
• Bachelor’s degree required, Master’s preferred and at least 4 years’ experience in database development, maintenance and manipulation is required
• Proficiency in Microsoft Access, Microsoft Excel, SPSS or other statistical package required
• Education and or experience in one or more of the following are preferred: healthcare software packages, performance improvement or care management, outcomes analysis, utilization management and project management. An equivalent combination of education and experience may be substituted
• Knowledge of and competency in a variety of computer software programs including Access, Excel and other software packages
• Knowledge of performance improvement concepts
• Bachelor's degree in computer or related field
• 6+ years of experience
• 2+ years experience performing advanced ETL development using SSIS including various dataflow transformation tasks
• Generate business logic, custom queries, and reports from software applications using Microsoft T-SQL per defined technical specifications
• Continually evaluate Microsoft T-SQL procedure performance and enhance the performance as required
• Performs complex custom analytics and develops solutions to complex software design
• Manage the extraction, transformation, and population of data files and databases (Microsoft SQL Server, Excel, Access, etc.)
• The Senior Data Analyst must possess a Master's degree in Computer Science, Engineering, or related field of study plus 3 years of experience in the job offered or 3 years of experience as a Developer or a related role. In lieu of a Master's degree plus 3 years of experience, Employer is willing to accept a Bachelor's degree in Computer Science, Engineering, or related field of study, or related plus 5 years of experience in the job offered or 5 years of experience as a Developer or a related role. All applicants must have at least 3 years (5 years if in possession of a relevant Bachelor's degree) of demonstrated experience developing and supporting database-driven applications using T-SQL on SQL Server 2000/2005/2008
• All applicants must also have demonstrated experience with: (1) using reporting software technology (e.g., SQL Server Reporting Services, Crystal Reports, Cognos, or similar tools), (2) managing developed code in a .NET environment (e.g., C#, VB.NET, etc.), (3) business process automation, (4) extensive scripting (e.g., SQL, PowerShell), (5) working in a production environment, (6) using source control management (e.g., TFS, SVN, etc.), (7) changing control management activities to support UAT and production deployments, and (8) server performance tuning
• Designs standard and custom reports/dashboards that are prepared for use by Operations, Performing Rights/Writer Publisher Relations, Licensing, Legal, Senior Management, and external customers (audio and a/v sources)
• Presents detailed analysis to BMI management; written and verbal
• Provides in-depth analysis of key Business data, and help form actionable recommendations to be used by Department and Senior Management
• Leads detailed analyses of music share processing, performance metrics, distribution analytics, and applications
• Assists in developing, creating, testing, and generating routine analytical reports and custom business analysis using Business Intelligence tools and SQL
• Works closely with departments throughout organization to produce actionable analysis related to music usage, performance data, and historical trending of key business metrics
• Collects, prepares, adjusts and analyzes quarterly and annual music usage data as obtained from Royalty Distribution processing files
• Develops improved methods and recommendations for music use analysis
• Converts files from various computer platforms such as mainframe, UNIX and PC
• Maintains databases that are used by this department for music use and statistical research and analysis
• Conducts research to gather information from a variety of sources, including BMI internal databases, the Internet and 3rd party data providers
• Attend meetings
• Assist in department projects in areas outside of regular workload
• Good communication skills, both written and verbal
• Must have knowledge of data processing concepts, basic statistics, and database concepts
• Ability to write reports and business correspondence
• Ability to effectively present information and respond to questions
• Mathematical, statistical, and analytical aptitude – good at problem identification and solving
• Above average ability with BI reporting tools such as Cognos, QLIK, Tableau, MS SSRS; advanced preferred
• Solid SQL query writing skills
• 4 plus years of relevant experience in the financial management industry and/or a technology role within the financial management industry
• Knowledge of business functions and workflows usually obtained through related work experience in the following areas: financial operations, portfolio and project management, technology projects. SQL skills strongly preferred
• An understanding of financial instruments and attributes of each security type, and an understanding of data governance functions
• An understanding of data, data movement, and data quality
• Goal oriented team player willing to work with a global group of professionals across Northern Trust Asset Management as a whole
• Lead, manage, and evolve the support and community reporting needs of our Self Serve platforms, including development of Tableau Dashboards, Site Catalyst Reports, and Data Warehouse Extracts
• Facilitate Mobile First reporting and validate accuracy of information flowing into and out of both Data Warehouse and Adobe Site Catalyst
• Partner with our IT teams to understand data feeds from various sources into Data Warehouse for use in different reporting platforms, including SSAS Cubes
• Manage internal/external reporting requests related to the performance of self serve metrics such as CIR, Engagement, among others
• Partner closely with Operations and IT teams and be centrally involved in site enhancements, app development, etc to ensure reporting requirements are met upon implementation as they come down the pipeline
• Work closely with other Digital Analytics teams to understand site tagging in place, being implemented, or being retired to align and prioritize deliverables from leadership
• 5+ Years Experience with SQL (Teradata a Plus)
• Experience with Site Catalyst (or other web traffic tools such as Google Analytics) required
• Wireless industry knowledge a plus
• Knowledge of digital analytics, metrics, and KPIs a big plus
• Excellent communication skills (written, verbal, presentation)
• Advanced knowledge of Excel (macro creation, automation, etc) a plus
• Experience with creating insightful reports consumed by a wide audience
• Ability to quickly learn and adapt to new technologies
• Strong interpersonal skills with the ability to lead coordinated efforts among various teams
• Ability to excel in a fast paced high impact environment
• Ability to manage multiple multi-faceted projects and prioritize work to meet deliverables
• A bachelor's degree computer science, business, engineering or a related discipline and approximately 6 years of related work experience; or a graduate degree and approximately 5 years of related work experience
• Prior Business analytics or Consulting experience
• Excellent facilitation skills that allow for business requirements consolidation and finalization
• Familiar with US and Canadian data privacy laws pertaining to HR/employee information
• Comprehensive data warehouse analysis and design experience, with full knowledge of data warehouse methodologies and data modeling
• Proficient in one or more of major ETL (Export Transform Load), BI Reporting, OLAP (Online Analytical Processing) and Data Modeling tools such as SAS, Cognos, Business Objects, Hyperion
• Sound knowledge of business intelligence products, best-practices and implementation methodology
• Strong ability to analyze user requirements and build front-end BI applications according to specifications
• Ability to be strategic, tactical and operational at any given moment of time
• Experience working with business to understand reporting requirements, global requirement consolidation, detail design and overall performance and scalability from data model perspective
• Effective leadership, project management and teamwork skills while being able to manage and support a team
• Ability to cultivate effective working relationships with colleagues, stakeholders and service providers at all levels
• Ability to advise, recommend and present requirements and solutions to complex problems and cope with ambiguity
• Analyze, review, forecast, and trend complex data
• Develop recommended business solutions through research and analysis of data and business process and implement when appropriate
• Experience with extracting source data and manipulating it into meaningful information/reports
• 3+ year of experience in business / finance analysis
• 3+ years in a reporting and analytic role
• 1+ year of experience with extracting source data and manipulating it into meaningful information / reports
• 1+ year of experience gathering requirements from the client / business and documenting
• Advanced level of proficiency with PC based software programs and automated database management systems required (Excel, Access, PowerPoint)
• Intermediate experience in SQL, SQL Reporting Services, or equivalent data capture / reporting tools
• Intermediate level understanding of ODBC, and MS excel (VBA, macros)
• 1+ year of experience developing and modifying queries of source data from a variety of applications to create accurate and timely reports upon request
• Experience Call Center data sets, metrics and systems
• Excellent analytical and problem solving capabilities with special attention to accuracy and detail
• Architect/Design Data Warehouse infrastructure and solutions
• Develop, enhance, integrate Data Warehouses/Data Marts and Business Intelligence Solutions
• Test Data Warehouses/Data Marts
• Deploy and Maintain Data Warehouses/Data Marts
• 2+ years of Visual Basic development experience
• 3+ years of SQL experience
• Visual Studio or other OO languages
• Navigate a complex data environment to produce information needed in response to regulatory exams and inquiries
• Work with business partners to develop and refine standardized data production processes
• Understanding of various financial products, including mutual funds, equities, bonds and annuities
• Experience working within complex financial services data environments is required, 7-10 years’ experience with a broker-dealer is preferred
• Strong SQL experience and understanding of relational databases – both MS SQL Server and Oracle
• Capable of effectively planning, prioritizing and executing multiple tasks concurrently, consistently meet established deadlines, and deliver exceptional results
• Able to work independently in a fast paced and dynamic environment
• Support the integration of environmental sustainability requirements into sector innovation processes (Stage Gate)
• Establish a global database for Life Cycle Assessment results to support and inform product innovation and supply chain decision-making
• Greenhouse Gas Emissions Goal Support
• 7+ yrs experience in data management and analytics, programming and/or IT with specific experience in managing information and reporting in a commercial environment
• Packaging experience/exposure preferred. Understanding of procurement/supply chain processes and responsibilities preferred. This role can virtual for the right candidate
• Clear and analytical thinker with the ability to identify process improvement opportunities and visualize "white space" data management and reporting solutions given specific functional requirements. Ability to quickly learn (execute and troubleshoot) new software/programs
• Analyze large structured and unstructured datasets across multiple channels, for multiple products, using numerous and diverse automated systems to identify or confirm theft, fraud or non-compliance with Corporate policies and procedures
• Provide professional analytical expertise through data mining, pattern analysis techniques and reverse engineering that will support evidence based investigations and/or assessments of Corporate processes
• Prepare evidence based reports and documentation in support of investigations into incidents of theft and/or fraud that if necessary, will meet the evidentiary standards of the judicial system
• Participate in a wide ranging variety of projects as assigned, either independently or as a team member, and where it will be expected, your analytical and data investigative skill sets will contribute to the success of the project
• Possess a functional understanding of the various point of sale systems and related transactional sale/product return/refund processes within the various CTC banners, PartSource, Marks, Petroleum, SportChek and Canadian Tire
• Act as the primary support for investigators during store investigations, with an understanding that investigations are constantly evolving and occasionally may require additional analysis and documentation preparation on an urgent basis
• Actively support and foster a diverse work environment that emphasizes high performance, teamwork and professionalism
• Assist in OSINT gathering and possess a strong understanding of methods used to in the collection of open source materials
• Partner and collaborate with business leadership on complex, single and multi-variable research questions to yield insight and a more informed decision making process by using a combination of structured and unstructured data
• Engages with project sponsors and stakeholders to understand the business question. Probes for hidden questions and goals. Helps bring structure to each request and translates requirements into an analytical approach
• Lead with advanced tools such as regression, hypothesis testing, and control charts. Demonstrates independence and proactive thinking while pursuing and promoting discussion that will lead to greater client insight, optimized performance, enhanced engagement, and improved retention
• Communicate results, interpretations, and conclusions in a manner that maximizes the understanding of others. Makes the case for change, sizes the opportunity area, and when necessary influence the audience off of traditionally held perspectives
• Manage a portfolio of work to ensure timelines are met and clients are informed of progress. Work with business partners and supervisor to ensure appropriate prioritization of work
• Aid the analytical development of Reporting Analysts and Data Administrators through structured coaching and development sessions. Assist them with getting up the learning curve
• Partner with other internal data user groups such as Client Insight and RDS to ensure the existing data infrastructure environment is capable of supporting analytical questions and to further enhance that capability when opportunities arise
• Gathers data across channels (e.g. web, phone, mail, email) when applicable to ensure a complete understanding of client behavior and potential opportunities
• Initiates, develops, and implements improvements to enhance departmental capability. Seeks to maximize automation
• Identify, implement, and support thorough testing and quality controls to ensure only the highest quality outputs are delivered to our clients
• Ensures that client needs are met in a thorough manner through maintaining a deep understanding of all data sources including but not limited to Cognos, Enterprise tables, and Retail Data Warehouse. Can successfully leverage various tools for report development (e.g. building queries from scratch in Cognos including basic joins, Excel, and Access). When applicable, uses knowledge depth / experience to troubleshoot any / all issues associated with data gathering and availability
• Undergraduate degree or an equivalent combination of training and experience
• Minimum of 3 years work experience in an analyst role preferred
• Strong client relationship management skills, able to collaborate on requirements and influence when applicable
• Experience with advanced analytical tools (e.g. regression, hypothesis testing tools, etc.), able to apply a logical problem solving approach to complex situations
• Solid knowledge of reporting tools to include; Excel (includes macro proficiency), Access, Cognos, Enterprise tables, Retail Data Warehouse, and Minitab
• Proven ability to work effectively and independently with strong time management skills
• Understanding portfolio liquidation performance trends through creation of MI and Insight for internal TDX stakeholders, clients, and suppliers
• Creating and executing innovative strategies to enhance portfolio performance, in line with the TDX test & learn framework
• Providing analytical insight and recommendations to the Agency Management and Client Relationship teams to optimize portfolio performance
• Effectively integrating into the analysis team and proactively manage relationships with stakeholders across all business function
• 5-7 years relevant experience
• Advanced knowledge of the technical environment/tools for own area
• Consulted as expert subject matter expert in at least one area of discipline to support clients/or project teams with research, analysis, design, hardware/ software support, solutions development and testing
• Capacity and eagerness to work independently as a senior/lead role on multiple tasks, and also coach/educate/guide/direct others
• Ability to assume assignments that are moderate- to highly- complex and multi-faceted, to be performed under management guidance
• The Sr Data Analyst's primary responsibility will be to receive and solve analytical business problems posed by all levels of management top to bottom including C-Suite to operations at WebMD. The topics of discussion will cover finance, marketing, and operations
• Meet with marketing, project and product management staff, at all levels, to understand goals and data sources such as
• 3 + years’ experience in financial or marketing analysis
• Bachelors degree in economics, finance, marketing/relateble filed or 4 years equivalent experience
• Strong database analysis experience
• Excel and database analysis skills (e.g. Access, SQL, Oracle)
• Comfortable with PowerPoint and making presentations to large and small groups in planned and ad hoc environments
• Ability to explain complex quantitative analyses to senior management
• Excellent organization and documentation skills
• Strong ability to multi-task in a fast-paced environment
• Strong ability to be responsible, accountable and result-driven
• Development of prototype solutions, mathematical models, algorithms, machine learning techniques, and robust analytics to support analytic insights and visualization of complex data sets
• Provide optimization recommendations that drive KPIs established by product, marketing, operations, PR teams, and others
• Drive innovation by exploring new experimentation methods and statistical techniques that could sharpen or speed up our product decision-making processes
• Desire to participate in an “Open Source” learning environment where sharing, documenting, teaching, and collaborating with others is the culture
• 5+ years relevant experience with a proven track record of leveraging analytics to drive significant business impact
• Bachelor's degree in Statistics, Mathematics, Operations Research, Computer Science, Econometrics or related field
• Statistical knowledge and intuition - ideally utilized in A/B testing
• Experience with distributed databases and query languages like Hive, Spark, Scala, or Pig
• Programming experience with a scripting language such as Python, Perl, Java, or Ruby
• Proficiency with a statistical analysis tool such as R or SAS
• Relational, no-SQL, and/or columnar data experience required
• Develop a deep understanding of engagement and retention drivers by persona/journey and provide insight on how to maximize return against key business metrics
• Build recommendations on effective customer journeys and provide product improvement opportunities that increase sales and adoption
• Analyze consumer behaviors, expressed preferences, and response to media and marketing efforts
• Apply analytical skills to develop more advanced solutions that drive action in the business
• Bachelor’s Degree and 5 or more years of experience analyzing massive sets of technical transactional data
• Experience constructing Boolean and SQL-based queries
• Advanced Excel skills for analysis, dashboarding, and data manipulation pivot tables, conditional statements, VLOOKUP, statistical packages, macros, correlations/regressions
• Strong visualization skills (Tableau, D3, web apps)
• Experience collaborating with and articulating recommendations to sophisticated technical audiences
• Confidence to take ownership of projects and make decisions in a fast-paced environment with minimal documentation and process
• Experience in digital, mobile, and/or VOD services
• Experience in digital entertainment industries
• Prepare and maintain analytics around functional headcount, revenue, COGS, and operating expenses by function, company and jurisdiction
• Develop and maintain analytical models that
• Bachelor’s degree in Finance, Economics, Statistics and/or Accounting
• Minimum 3-4 years in a financial analyst role, working with global companies
• Strong mathematical/analytical background with ability to understand complex data and solve difficult problems
• Highly motivated self-starter who can work with minimal supervision and guidance
• Strong written and verbal English communications skills in order to articulate the results of the analytics and to draft memorandums
• Strong excel skills; access database skills preferable
• Experience using Essbase and Business Objects is preferable
• Results – and detailed – oriented with the ability to manage conflicting priorities effectively
• Ability to work in a team environment and effectively collaborate
• Experience in managing/directing junior staff is desirable
• Develop working solutions to custom client requirements and Data services automation requirements, keeping in mind product capabilities, scope limitations and the impact on integrated products employing SQL Server built in features and analytical methods
• Design specific databases for collection, tracking, and reporting of administrative clinical data and Operational Product Data for IT Operational performance analysis using SQL Server Management Studio 2008/2012 R2
• Design, code, test and debug custom SQL queries and generate financial, utilization, cost reports and IT Operational Performance metrics, using Microsoft SQL queries, SQL Server Management Studio and SQL Server Reporting Services
• Design, execute and implement IT Automation solutions and perform complex clinical and financial analytics as needed by clients and executive management, utilizing MS office suite and SQL database technologies
• Prepare documents and presentation materials describing multiplatform IT Automation design and solutions, analytic methods, observations and findings of analytics, and/or business logic flow employing MS office suite
• Perform root cause analysis to identify data flow issues/ system performance issues and/or data discrepancy issues of the IT Operations team
• Serve as an expert resource to develop and implement Operational performance tracking models, analytical and statistical models on large HealthCare-data bases
• Identify and Perform analytics on manual operational bottlenecks across various Product offerings for performance optimization and streamline IT operational deliveries
• Designs and develops software product applications for automating the manual Operational tasks across various Product offerings. Involved with full software development lifecycle including testing, implementation and auditing
• Diagnose and address issues as necessary and work with product team to implement correction plan
• Extensive latitude for independent judgment
• Ensures designs, code and processes are optimized for performance, scalability, security, reliability and maintainability
• Works without supervision on highly complex projects
• Assists less experienced peers with the Automation and Operational tasks, analytical functions and processes; and
• Use SQL Server Management Studio and SQL Server Reporting Services to design, develop and perform advanced-level Data Analysis in support of the product offerings
• 3 years of experience with analytic and data management or software development environment
• 3 years of experience with developing database driven projects using T-SQL or PL/SQL on SQL Server/Oracle
• 3 years of experience with involved or participated in the Automation initiatives
• 3 years of experience with MS Excel (intermediate/advanced level Excel incorporating visual basic, and/or excel macros), PowerPoint, Project, and SharePoint; and
• 3 years of experience with SQL database tools
• Conduct data analysis to provide insight into marketing and product opportunities within targeted consumer segments
• Conduct data analysis to answer specific business questions asked by clients and/or support teams; use data to establish facts and draw valid conclusions
• Synthesize analysis findings and communicate to internal partners to drive further understanding of the consumer lifecycle and ultimately influence revenue projections
• Manipulate data to make it usable for analysis by summarizing data points, creating new metrics, and addressing data quality issues
• Make recommendations to drive revenue and/or profitability growth, including creation of programs or initiatives, through independent thought based on analysis and a comprehensive understanding of the business
• Produce analysis that highlights current trends in the account base as well as identifying when trends are impacted by changes in subscriber behavior or other market forces
• Perform analysis in support of forecasting to identify trends, seasonality, and other demand impacting variations
• Respond to ad-hoc reporting requests, which may be well defined or posed more generally as a question, by gathering, manipulating, and analyzing data
• Under minimal supervision or direction, improves existing procedures and creates new Sales Operations policies and/or procedures
• Maintains written departmental standards and procedures
• 5+ years of business-focused analysis experience in a data analytic, information technology, finance or marketing role
• Must be able to analyze data/situations and present recommendations
• Must be process and efficiency focused
• Expert user of both Microsoft Excel and Microsoft Access. Must be able to produce reports and documentation using advanced Microsoft Excel and Access functionality (i.e. pivot tables, table merges, interactive forms etc.)
• VBA/SQL knowledge a must
• Excellent writing, editing, communications, organizational, and decision making skills
• A strong understanding of database usage, management, and best practices
• Ability to learn and utilize various software applications related to the position
• Data management and analysis capabilities, including the ability to design and develop data extraction and transformation solutions
• General business acumen
• Gather and analyze business requirements from business process owners, document functional requirements, develop/recommend solutions and identify any potential change impacts
• Assist in leading the adoption of Kiewit’s project information database, Cosential, across the company
• Work with developers to define requirements and test solutions
• Provide training and coaching to support team, project team and end users
• Assist the OFA with coordinating with KTG for Cosential integrations including TED, PI, CRM, and EDW
• Conduct testing of system updates specific to marketing/proposal teams (validating business processes as necessary)
• Ensure proper communication to all levels of the organization
• Complete a variety of work assignments (project as well as support) within structured deadlines
• Follow corporate project management procedures
• Able to work independently, evaluate risk, communicate and escalate issues to manager
• A good team player and collaborative worker with a positive attitude
• Good interpersonal skills to assist with communications
• Ability to work on a number of deadline driven projects simultaneously with a sense of urgency
• Strong communication, analytical, time management, organizational skills and detailed oriented
• Global Data, Insights and Analytic (GDI&A) Team is a new and rapidly expanding group
• The GDI&A Data Operations is responsible for the discovery and curation of new and existing data sources (First party data, external data providers, public data, social media, digital exhaust, transactional data etc.) for use in building incremental value and insight for the business
• The Data Acquisition Specialist is responsible for the global research, documentation, testing and acquisition of external data assets, aligned to internal customer needs
• This position is responsible for the evaluation and profiling of external data sources
• Analyze new and existing external data sources to suggest fit for use cases
• Collaborate with Analytics and IT teams to profile the data for eventual use in modeling and visualizations
• Able to identify relationships in data to assist in providing insights
• Enhancements to the external data & vendor knowledge system
• Establish relationships with vendor technical points of contact and internal customers
• Work cross-functionally to manage data and analytic projects
• Improve department results through innovation
• Evaluation of data accuracy, completeness, timeliness and stability and establishing repeatable, sustainable processes to maintain data
• Develop business controls to comply with legal and regulatory requirements and corporate policies
• Demonstrated SQL and Alteryx skills. (SAS or Tableau accepted as alternatives)
• Strong experience in profiling data
• An understanding of creatively visually depicting data
• Strong collaboration and presentation skills
• A passion for embracing innovation, discovery & constant learning
• Demonstrated problem formulation and problem solving skills
• Bachelor’s Degree 2 or more years of experience with using at least one of the following data analysis tools: SAS, Hive, Alteryx, Hadoop, SQL or QlikView
• 3 or more years of PowerPoint and Excel experience
• 3 or more years of analysis, computational complexity and critical problem solving
• Enhance and re-engineer sophistication of monitoring tools and quality control checks for continuous process improvement and operational efficiencies
• Implement the performance enhancing practices within/across teams
• Gather and/or clarify requirements for customized data analysis, reporting, and data extracts
• Perform the resulting SQL development and deliver validated results
• Configure new parameters and processing runs to identify and implement relevant operational metrics and informal and formal status reporting for management
• Validate successful completion of processing runs through established quality control checks, leading advanced troubleshooting of processing and reporting errors often as the second level of diagnosing, researching, and addressing operational data requests; and
• Engage in the release of new revised code to the production environments
• Master's degree in Computer Science, Engineering, or related field of study, plus at least 3 years of experience in the job offered or 3 years of experience in IT-related occupation. In lieu of the Master's degree plus 3 years of experience, Employer will also accept a Bachelor's degree in Computer Science, Engineering, or related field of study, plus at least 5 years of experience in the job offered or 5 years of experience in IT-related occupation
• All applicants must have demonstrated experience with: (1) T-SQL debugging; (2) SQL performance tuning techniques; (3) developing managed code in a .NET development (e.g., C#, VB.NET, etc.); (4) business process automation; (5) scripting experience (e.g., SQL, PowerShell); (6) working in a production environment; (7) source control (e.g., TFS, SVN, etc.); (8) change control surrounding UAT and production; and (9) ETL processing
• Bachelor’s degree required, Master’s degree preferred. Educational background (and/or experience) emphasizing quantitative skills and research methods (e.g. Mathematics, Statistics, Social Science etc.); 4 years of related experience or equivalent combination of education and experience
• Excellent analytical reasoning and problem solving skills; ability to compile, analyze and interpret data
• Ability to produce both descriptive and inferential statistical analyses; proficiency in a programmable statistical analysis software (Base SAS, SPSS syntax, STATA, etc-SAS strongly preferred)
• Demonstrated ability to use various other software packages such as Microsoft Office products (Excel, Word, PowerPoint, etc.)
• Demonstrated understanding of relational databases and SQL
• Excellent interpersonal, verbal, written, and visual communication skills
• Ability to convey complicated data and complex statistical results as organized and easily understandable information
• Experience with exploratory analysis and graphic visualization tools such as Tableau or QlikView
• Excellent organizational skills, including a keen orientation to detail and deadlines, as well as the ability to prioritize work and handle multiple tasks simultaneously
• Ability to handle confidential materials professionally and to utilize discretion in releasing confidential information
• Ability to maintain accurate and detailed records and documentation
• Ability and desire to acquire new knowledge and skills independently
• Ability to work independently as well as be part of a team
• Identify opportunities for expanded OCD capabilities include best-in-class shopper segmentation, shopper intelligence platform, online and offline marketing, personalization and relevancy across all elements of the marketing mix (from e-circ to targeted direct mail/email, to personalized content), retail strategy and digital strategy, and advanced analytics in support of both the marketing and merchandising functions
• Work with client partners and product strategy leads to tailor proposals and pricing to identified opportunities
• Assist in the client-facing delivery of expanded analytic capabilities where appropriate
• 8+ years of demonstrated success in analytic leadership and/or analytic consulting roles in the field of marketing analytics, media analytics, marketing research, direct marketing, or analytic function at a leading CPG Retailer
• BA or BS in Economics, Mathematics, Statistics or equivalent quantitative discipline. MS or MBA with business analysis or quantitative focus preferred
• Experience working with CPG Retailers and high proficiency leveraging shopper behavior datasets
• Hands-on experience conducting analyses that interrogate large, diverse datasets, and translating findings into practical and actionable business decisions. This is a hybrid role, requiring a combination of hands-on analytic capability, the ability to effectively communicate complex analytics in a simple, client-friendly way, and the ability to use data to formulate actionable business recommendations
• Experience in the digital media space, including analysis of online consumer behavioral data, targeting, digital measurement and/or attribution, etc. highly preferred
• Success leading client relationships focused on utilizing data to enable decision-making, with strong presentation skills and experience interacting with CPG Retail clients across a range of functions (marketing, analytics/insights, media planning etc.) and levels (manager to director to C-level)
• Experience using analytics software packages to run and QC statistical models. Specific coding/programming experience is not mandatory, but will strengthen consideration
• Ability to work in a demanding, fast-paced and dynamic work environment
• Demonstrated success in driving successful client and business outcomes in an environment where multiple stakeholders have separate interests and objectives
• 7+ years of BizTalk architecture,design,implementation,and/or support of highly distributed and large scale applications
• Solid understanding of BizTalk components and setup including BAM,BRE, Maps/Transformations, Pipeline components, and Adapters
• 5+ years of experience in BizTalk ESB architecture, message queueing,pub/sub models, common integration principles, and best practices. Strong knowledge of SOA,EAI and B2B integration design patterns
• 5+ years of experience in developing and integration with webservices APIs. Strong knowledge of related technologies - WCF,WPF,IIS,REST,SOAP,XML,XSD,XSLT and JSON
• 5+ experience with requirements gathering, creating specifications, business process diagrams, collaboration with business, infrastructure and technical teams ;Ability to analyze requirements and propose innovative but workable solutions
• 2+ experience in the analysis, design and migration of BizTalk solutions – from Biztalk to higher version of Biztalk or Biztalk to other technologies
• Knowledge of RDBMS systems and CRUD operations – MS SQL Server 2012
• 2+ experience working with Agile methodologies
• 2+ experience with Team Foundation Server(source control, automated builds)
• Experience working with testing tools – Nunit, Microsoft Test Manager
• Certification in BizTalk 2010 or 2013 R2 or previous BizTalk certifications is highly desirable
• Experience working with Java integration tools – preferably Mulesoft
• Experience migrating BizTalk solutions to another technology/tool is highly desirable
• Some experience with Pharma/Biotech industry preferred
• Analyzes data and insights using spend analysis tool (an IT capability used to understand trends in spend by category, supplier, and division, and predict optimal pricing and supplier partnership options). Develops creative, technically sound recommendations and data reports on processes, business, client and crew performance to department management
• Partners with the Data Services Manager in the strategic and technical direction of Shared Services Data team
• Consults with internal clients and interprets requests for information to determine appropriate sources of information and data mining techniques to be employed
• Support Category Managers (and teams) in ad-hoc data analysis in support of category strategy development and savings generation (e.g. should cost analysis)
• Develops strong working knowledge of data sources and data mining tools
• Reviews end product with the requestor to ensure adequate understanding. Provides data analysis guidance as required
• Documents project deliverables, including but not limited to program descriptions, run instructions, and run frequency, paying attention to team guidelines
• Minimum of four years' experience in data mining, data analysis, data management, and data stewardship
• Advanced experience with data modeling concepts, database design for relational and multi-relational databases (minimum one year)
• Advanced knowledge of advanced analytical tools (e.g., regression, hypothesis testing tools) and current versions of the Microsoft Office Suite (specifically Excel and Access), including VBA
• Strong, demonstrated analysis and problem-solving skills
• Formal training in computer programming
• College degree in Computer Science (CS), Information Management (IM), Information Systems (IS) or related discipline
• Minor in Business, Finance, Economics or Statistics or Mathematics a plus
• Business/Finance or related degree with a minor in (CS, IM or IS) is also acceptable with tangible work experience
• At least 1 year of experience working with Fixed Income data and/or Fixed Income markets
• Technical Skills: Proficient with SQL query writing in a relational database environment (Sybase or SQL Server preferred)
• Knowledge of ODBC or other data interface APIs
• Intermediate to advanced knowledge of MS Access and MS Excel (exposure to advanced macro writing using VBA)
• Familiar with the software development life cycle
• Familiar with ETL tools, SSIS is a plus. Prior experience with a business intelligence/reporting tool is a plus
• In depth ability to grasp both business and technical processes and concepts
• Excellent written/oral communication and interpersonal skills with a strong ability to effectively communicate both technical and business terms
• Demonstrated ability to coordinate multiple projects and priorities simultaneously
• Business analysis experience is a plus
• Well organized, efficient and detail oriented
• Strong sense of accountability, and a strong work ethic
• Ability to research technical aspects and resolve problems with minimal supervision
• Develop proactive data strategies and present recommendations to leadership and identified audiences regarding the market, competition, and our position in the market place
• Complete accurate and timely metrics and reporting. Research, analyze, and validate the primary source(s) for definitive data and completeness to feed metrics associated with Retirement Investment Services
• Effectively utilize complex computer programs to mine data sources providing relevant information in an easily consumable manner
• Lead project team members to thoroughly develop and maintain processes or systems in accordance with scheduled target dates
• Perform other job related duties or special projects as required
• Gather business requirements for analytical applications in iterative/agile development model
• Create source-to-target mapping based on requirements
• Create rules definitions, data profiling and transformation logic
• Gather and prepare analysis based on requirements from internal and external sources to evaluate and demonstrate program effectiveness and efficiency, and problem solving
• Support Data Governance activities and be responsible for data integrity
• Develop scalable reporting processes and querying data sources to conduct ad hoc analyses/detailed data profiling
• Research complex functional data/analytical issues
• Assume responsibility for data integrity, data quality among various internal groups and/or between internal and external sources
• Provide source system analysis and perform gap analysis between source and target systems
• Make recommendations for data warehouse / mart design
• 3 or more years of data reporting experience
• 3 or more years of data analysis experience
• 3 or more years of systems analysis experience
• 3+ years of experience with ETL tools
• 1+ year of healthcare industry/claims data experience
• Data modeling and data architecture experience
• Experience organizing, sorting and filtering data in order to distinguish patterns and recognize trends
• Experience in data profiling/analysis with Big Data/Hadoop processing environment
• Experience developing innovative approaches
• 3-5 years’ experience in a data analytics position
• 2+ years’ experience using database management systems (DMBS) using SQL to create, query and join tables
• Demonstrated knowledge of structured data, such as entities, hierarchies, relationships and/or metadata, and ability to profile such data
• Experience/proficiency with Microsoft Excel and PowerPoint
• Experience using tools / platforms such as: Tableau, Hadoop, OBIEE, Access, or similar
• Experience with the following systems: OMNI, systems and databases used within TIAA
• Familiarity with Big Data concepts and terminology
• Financial Services experience desired
• Ability to combine data from multiple sources when needed for the analysis
• Familiarity with data management best practices
• Timely delivery of analysis, reports and presentations to support business reviews
• Communication and interpersonal skills
• Design dashboards, scorecards, and other tableau visualizations highlighting progress on but not limited to Data Centre Strategy, Workload Placement and Currency related initiatives
• Extensive SQL query skills to leverage DataMart to produce tableau dashboard reporting
• Provide technical leadership across a broad range of data analysis functions including data modeling, report design (utilizing tableau), structured query language (SQL), data quality, data profiling, metadata enrichment and management, data provenance and lineage and other specialized data management functions
• Work independently as a senior lead and may manage and direct activities related to analysis, design and support of technical data management solutions on various projects
• Extensive experience with Tableau reporting
• Functional/technical proficiency with at least 4+ full lifecycle SAP implementations and 8+ years of industry and/or consulting experience
• At least 8 years of SAP experience implementing SAP MDG
• SAP SD, MM. PM, and or MDG experience a plus
• Experience defining systems strategy, developing systems requirements, designing and prototyping, testing, training, defining support procedures and implementing practical business solutions under multiple deadlines
• Adept at designing and implementing technology-enabled business solutions for clients as part of a high-talent team and as a team lead or Project Manager on at least 3+ full cycle implementations
• Able to collaborate with clients, identify engagement follow-on opportunities and have a strong desire to excel and be committed to gaining exposure to multiple industries while further developing your career
• Strong current hands-on configuration and design skills
• Hands on experience with multiple databases - Oracle, Sybase, Informix
• Hands on experience with no sql databases like Mongo DB
• Proficient with database architectures
• Knowledge on Java/JEE enterprise application architecture
• Proficient with PL/SQL, stored procedures and views
• Proficient with troubleshooting performance problems and solution recommendations for optimizing performance
• Fine Tune database configurations
• Respond to all tickets assigned to our team
• Monitor databases checking for any problems
• Set up database backup and recovery jobs for new databases
• Install database engine on new database servers; Install database client software on workstations
• Create and maintain Disaster Recovery Procedures; Participate in Disaster Recovery tests
• Perform production database recoveries; Perform refresh of development and QA environments
• Setup new database IDs and perform password resets
• Consult on database design for new applications; Consult on database design for application changes and/or enhancements; Consult/assist developers with database access and data retrieval
• Trouble shoot database issues; Apply database patches, updates and install new versions of database
• We support multiple Customers on a daily basis
• Attend CAB meetings; Provide On-call support
• Cloning databases as per Service Requests; Carry out Regular maintenance activities to ensure optimal database performance
• Qualification: Bachelor’s degree and/or required years of experience
• 8-10 Years of work experience
• Must have experience in Technical Process Expertise
• Should be proficient in Technology Application and Technical Solution Design
• Should have progressing skills in Continuous (Service) Improvement and Transition Management
• Data analyst for business intelligence
• Become an expert and train and support internal customers in Customer Service Operations in the suite of data based business intelligence products we are developing
• Lead and participate in beta tests and pilots of new business intelligence services
• Manage escalations with these services and drive requirements and issues back into the IT organization responsible for the underlying data framework and toolset
• Experience working on business analytics/intelligence preferably in a large organization, in a role between software engineering and the end consumer of business data
• Skill in the manipulation of large complex data sets, knowledge of one or more database query tools e.g. SQL. familiarity with statistical analysis e.g. hypothesis testing, regression, cluster analysis etc
• Demonstrated experience and ability to lead cross-functional projects and develop organizational metrics
• Networking capabilities within multi-national, cross-organizational and geographically distributed teams
• Ability to explain complex technical matters to a non-expert audience
• Work with key stakeholders in development and execution of market research studies with a focus on life science products
• Statistical analysis of data, including analysis of customer segmentation and conjoint studies
• Interface with finance and portfolio managers to develop financial forecasts and track key metrics for new product initiatives
• Document and present analytically derived results to internal business partners
• Perform all lifecycle maintenance services in a timely and accurate manner as required throughout the day
• Prompt and accurate data maintenance in RefData and Confirms systems, ensuring necessary controls are adhered to
• Assist trading operators and ISP support in resolving contractual queries arising day to day
• Prompt reporting and resolution of any mismatch of data/terms within the back office systems and any other source of information relevant to the trade
• Accountable for resolving queries with Settlements and other internal departments
• Develop and maintain robust Front Office and stakeholder relationships
• Understand the role risk profile and, in conjunction with the Data and Confirms Operations Delivery Manager, identify and mitigate operational risk issues
• Assist the Team Lead to meet the SLAs between the Data Execution team and its customers through use of the appropriate metrics and KPIs
• Ensure compliance with regulatory and legal requirements and ensure current business good practice is employed in the team
• 2-3 years of working experience in similar environment
• Master Data experience is an advantage
• Ability to be accurate with good attention to detail
• Ability to prioritize work and be organized, to multi-task, to work under pressure and comply with strict SLA’s
• Ability to understand the end-to-end processes and how actions may impact them
• Ability to understand the flow of data between systems and how changes may impact the business
• Good understanding of systems and data structures
• Bachelor’s degree in Business Administration, Computer Science or relevant discipline; or equivalent work experience
• Strong data analysis skills. Strong experience with reporting analysis and systems analysis
• Experience in data warehousing. Demonstrated knowledge and experience in requirements gathering and development
• Has a solid level of understanding of multiple data sets, developing subject matter expertise
• Relational database design and development
• Experience with database and SQL server reporting service
• Understanding of Data warehouse architecture and design
• Strong understanding of data quality assurance processes and procedures
• Understands correlation of data
• Communicate technical information to a wide range of technical and non-technical audiences
• Evaluate marketing results, trends, tests, and provide variance and root cause analyses to support business decisions
• Translate large and complex data sets into actionable information
• Provide analysis and support for key initiatives and strategic projects
• Compiles, reviews, and presents complex marketing analyses to marketing managers/directors, identifying risks and opportunities
• Partners with a variety of different marketing areas to gather information, understand business issues and challenges
• Completes periodic sales and expense forecasts for advertising and direct marketing channels
• Develops/assesses gaps in the financial planning process and make improvements as necessary
• 3+ years Marketing Analytics, Forecasting, and/or Analysis experience
• Advanced knowledge of Microsoft Excel (must be able to use Pivot tables, v-look ups, charts, graphs, and create formulas)
• Experience using SAS and SQL tools for reporting and data manipulation
• Experience working with large scale data warehouses
• Bachelors Degree in Business, Finance, Economics, or Statistics
• Strong written and verbal communication skills are required
• Ability to work in a rapidly changing environment and possess the ability to work collaboratively and influence across a matrix environment
• Able to demonstrate an understanding of how core business drivers influence financial results
• Prior experience working with marketing mix tools
• Prior experience working with digital attribution technologies
• Experience forecasting marketing campaigns
• Familiarity with Health Insurance products
• Understanding and documenting business needs for large scale change initiatives, including data flow design, clinical program design and high level technology requirements
• Interprets requirements and translates them into data requirements (interfaces, data transformation, etc.) for complex projects
• Data mapping (e.g. between source and target databases; mapping screen fields to database columns)
• Determining how existing technology and data solutions will need to change to support evolving business needs
• Evaluate system changes for downstream system, reporting and / or organizational impacts
• Identify and document as needed, current state processes and develop future state processes and procedures to support projects as appropriate for a variety of functional and operational areas, alone or in concert with other project team members
• Become a business subject matter expert on Clinical Data Flows and integrated data assets (data stores, data warehouses)
• Lead group meetings, provide agendas, and follow up with meeting minutes
• Appropriately escalate and communicate project status and issues to management for support and / or guidance
• Drive project execution for demonstrated results
• 4 years of experience as a business analyst, writing requirements, performing data analysis, and report development
• 2 years intermediate level of programming knowledge and of relational databases, database structures and design, systems design, data management, data warehouse
• Excellent leadership, communication, organizational, prioritization skills
• Demonstrated increasing responsibility for documenting and developing solution technology to support business problems
• Bachelor's degree or 5 years of experience as a Business Analyst in a clinical environment
• 5+ years equivalent experience in healthcare, hospital or insurance
• 4 years of experience with multiple software development life cycle methodologies and requirements documentation approaches (features, user stories, use cases, domain models, logical data models)
• Collaborate with Business product owners and technology to build and monitor analytic products that bring relevant property centric data the Financial Services Industry
• Experience and background with US Property data, the real estate industry, or financial services
• Perform data mining and query development in support of ad-hoc and strategic analysis
• Analyze data and identify data anomalies or patterns through your analysis that will provide more explanatory detail about US property data and predictive analytics
• Responsible for data importing, cleaning, transforming, validating or modeling data
• Create summary findings and present data in charts, graphs, tables, and summary formats
• Utilize tools to analyze, query and manipulate data according to defined business rules and procedures
• Proficient in excel, pivot tables and SQL query development
• Identify data quality issues and propose solutions which maximize automation and usage of data within the model
• May update/maintain database with reviewed and corrected data
• Critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level informationinto details, abstract up form low-level informaiton to a general understanding, and distinguish user requests from the udnerlying true needs
• Proactively communicate and collaborate with internal customers to analyze information needs and functional requirements
• Work independently with users to define concepts and under direction of product management
• Serves as the conduit between the internal product group and the software development team through which requirements flow
• Collaborate with developers and subject matter experts to establish the technical vision and analyze tradeoffs between usability and performance needs
• Owns customer vision and requirements full cycle – requirements, design, implementation, testing, user acceptance, deployment, and maintenance
• Latitude for independent judgement
• Ability to capture business requirements and tranlate them to the technical team
• Ability to create technical as well as end-user system documentation
• Experience working an an Agile/Scrum SDLC (desired)
• Experience working with credit & property data (desired)
• Work location in either Santa Ana, CA or Folsom, CA*
• Typically has 3-5 years of directly related experience
• Knowledge of required tools to query and manipulate data in varying formats including SQL, Excel
• Ability to follow and develop data quality standards, metrics and audit procedures
• Knowledge of databases, formation and manipulation
• Knowledge of programming
• Conveys complex technical issues/problems to programmers in a clear/concise manner. Must be familiar with basic data/programming terminology to communicate as much of problem and solution as possible
• Demonstrated foocus for customer satisfaction
• Able to manage client relationships
• Strong critical thinking, analytical and problem solving skills
• Good multi-tasking skills
• A strong drive for results
• Excellent influencing skills
• Detail oriented with strong organizational skills
• Excellent relationship management skills
• Objective, creative, and diplomatic team leader
• Excellent stakeholder engagement
• Using a variety of source systems, create and produce on a regular basis professional, detailed metric analysis reports related to all aspects of HRSC operations. Using a variety of reporting or analytics tools as well as Excel and PowerPoint, create professional ad hoc analyses, measures, or reports related to HR SC operations
• Field ad-hoc and project related reporting and analysis inquires by clarifying requirements and setting expectations for development time
• Present these metrics and analyses to HRSC management team along with insights or suggestions for interpretation or for follow up actions. Identify potential improvements based upon analyses
• Manage a metrics inventory including identifying and adding new metrics and documenting and maintaining the specification of all metrics in the inventory
• Monitor and analyze operational measures (routine and ad hoc) to watch for indications of issues or problems
• Learn and study HRSC industry benchmarks; compare HRSC metrics and data to these benchmarks and suggest follow up actions or areas of study
• Work collaboratively with HR systems groups (HR and IT&S) and HR analytics function to manage data and produce accurate and meaningful analyses
• Manage projects to implement process and technology improvements for the HRSC. Work with CPI team members to re-engineer processes that will streamline and automate HRSC functions; identify technology requirements; liaise with other functions, as required
• Deliver continuous process improvement training to HRSC staff on processes/programs supported by the HRSC; assist other team members in developing content and working with the L&OD Center of Excellence to develop training for impacted stakeholders
• Update the knowledgebase, when updates are available
• Update process documentation and desktop procedures
• 3-7 years of experience with quantitative analysis and statistics in a business environment
• Proficient use of Excel, including charts and graphs, pivot tables, and data connectivity; proficient use of PowerPoint
• Innately curious about how and why things work and tenacious in using data and facts to satisfy that curiosity
• Proficiency with SQL Server database development, stored procedures, views, and ETL
• HR service center, shared services center, or customer service center experience a plus
• Strong verbal and, written communication skills, excellent presentation skills
• Ability to handle multiple priorities, frequent change, and short deadlines
• Develop programs to monitor physician performance on clinical indicators using SAS and an internally developed Unified Expression Language based syntax
• Investigate issues in healthcare data from acquisition through presentation in the UI
• Implement analytic directives on healthcare data from senior staff and clients and develop reports as needed
• Assist in designing, documenting, programming and standardizing processes and reports
• Assist in clinical quality measure configuration
• Participate in quality assurance of clinical quality measures including test case creation, SAS/SQL/Unified Expression Language/XML code review, independent results validation, and pulling of sample cases from client data to support User Acceptance Testing
• 2 years of experience with healthcare data and large databases
• Advanced SAS programming skills, including proficiency in Base SAS, SAS MACROS, Stored Procedures, SAS/ACCESS to relational databases and Hadoop, and the SQL Pass Through Facility
• Must be analytical, detail oriented, and possess desire to advance and grow personally and professionally
• Ability to multi-task and manage multiple projects with varying timelines
• Experience with Unified Expression Language and HiveQL a plus
• Manage project and client relationship for small projects
• Extract actionable business insights from the data and build deliverables that clearly communicate the findings and recommendations
• Research industry metrics and business context and bring this context to bear in analyses
• Present findings and recommendations to internal clients
• Identify opportunities to create and automate repeatable analyses or build self-service tools for business users
• Propose R&D ideas that will address client strategic needs or advance ADP IP
• Contributes to team-wide efforts for achieving organizational goals, improving processes and knowledge sharing
• 2 to 5 years of experience in an analytical or quantitative role in areas such as consulting, planning, analytics, or data driven strategy
• Bachelor's Degree in quantitative field (Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent experience) is required
• Master's Degree in quantitative field will be given preference
• Experience in credit cards, financial services, merchant analytics (such as retail, hotels or airlines), or tech is helpful but not required
• Degree in Engineering, Statistics or related field preferred but not required
• Experience managing and analyzing KPI’s for a technical organization
• High level of comfort working with monitoring and metrics infrastructure
• Self-starter who is able to build consensus around goals beneficial to the organization
• Proven ability working within technical architecture and related end-to-end data flow
• General level of understanding of internet protocols
• In depth experience utilizing Excel, Tableau or other tools to effectively present graphs, dashboards and reports
• Familiarity with processing data via scripting languages (such as Python or other tools)
• Experience performing a similar role in a Development or Technical Operations organization is required
• Experience with Hadoop and Hive are preferred
• Partner with product managers, business insight analysts and data analysts on Personal Banking analytics initiatives
• Take ownership of and automate critical personal banking reports
• Serve as an expert on Personal Banking data and provide coding expertise and best practices to place context around data discovery linked to key analytics projects
• Provide data support to business users in partnership with the data governance and reporting team and ensure requirements regarding privacy and security of data and access controls are appropriately captured
• Build strong relationships with product partners and other key internal partners (Enterprise Analytics, Data Governance & Reporting, Customer Strategy, Marketing, etc.)
• Perform analysis, translating data into information and answering urgent business questions
• Develop and maintain knowledge of available data sources and data within personal banking platforms in partnership with data reporting and governance team
• Flexibility to adapt and manage within a fast-paced, dynamic business environment
• Strong interpersonal and communication skills, both written and verbal
• Strong organizational skills, with the ability to work in a fast paced environment and manage multiple deadlines and priorities
• Experience working in both a technical and business context and able to translate technical concepts into easy to understand business language
• Working knowledge of general banking / consumer finance products, policies and operations
• Analytics on DFS portfolio management data to ensure accuracy and consistency of data
• Aid in the operational management of DFS portfolio management data procurement
• Interact with Credit Bureaus to gather information on attributes and match rates
• Manage projects through entire project life cycle from initiating requirements through implementation and validation
• Analyze portfolio reporting data and identify inconsistencies with Credit Bureau Reporting policies
• Analyze data relating to customer complaints and disputes across DFS portfolios
• Leverage portfolio account management data and other internal data to conduct independent analysis
• Explore and implement process enhancements to improve efficiency and for continued monitoring of existing processes
• Coordinate initiatives with external and internal business partners
• Create dashboards and reports to present results of analysis to management
• 3-5 years of experience in analytics and data mining
• 2-3 years of experience in project management
• Extract data from various source systems and data stores by performing light business coding (Java/.NET, scripting, etc.)
• Meet with clients to conduct requirements gathering and perform validation in-person and over teleconference
• Map and transform data using various techniques (XSLT, SSIS, MapForce, etc.) based on client input and requirements
• Perform ad-hoc queries (SQL, LINQ, etc.) and reports to analyst client data before and after migration
• Load data into target system and perform validation to ensure no data is lost or corrupted
• Work with various teams to identify roadblocks, resolve issues, track go-live dates and ensure timely completion for each project
• Documenting details of projects in Salesforce/Jira and complete cleanup tasks
• Execute production data migrations (requires occasional evening/weekend work)
• Contribute to on-going development and refinement of data migration tools and processes
• Apply lessons to future projects and continuously improve the migration process
• Support Regional and Global efficiency driven initiatives
• Proactively identify opportunities to improve effectiveness of AML alerts
• Responsible for the data mining, manipulation, formulation and proposal of newly developed solution
• Analyze, prepare, present and interpret reporting or research results with recommendation to assist compliance and business users
• Candidate should demonstrate exceptional critical thinking skills and have experience in applying intelligence analysis to drive dynamic decisions
• Candidate should be well versed in applied research, quantitative and qualitative analysis (including multiple methods such as pattern or trend analysis, center of gravity or weighted centrality analysis, social network analysis, threat finance, targeting, etc.) to create intelligence from big data sets and drive decision recommendations
• Big data analysis and bolt on components (Hive, Spark, Platfora, Python, etc) experience a plus, but not required
• Candidate must have experience with data analysis, or have experience using statistical data methods and programs to develop intelligence analysis assessments and products; knowledge of data visualization a plus
• Experience with graph or network analysis software (I2 Analyst Notebook)
• 8+ years in intelligence or data analysis experience required
• Business experience, financial industry, technology, information management, computer science, business intelligence or data mining background preferred
• Bachelor’s Degree or additional equivalent work experience required (Computer Science, Computer Technology, Mathematics/Statistics, Engineering, Actuarial Sciences, Economics, Department of Defense or related intelligence discipline a plus)
• 5 years’ experience in reviewing, updating and evaluating Navy Training Management corporate database systems such as CeTARS and FLTMPS
• Must have ability to analyze data and detect trends as well as summarize findings, draw conclusions and put together presentations
• Demonstrated experience in the annual review of training requirements in support of the Program Objective Memorandum (POM) process
• Must be a US citizen and have active Secret clearance
• CAA Team Member
• 2+ years of experience with software development lifecycle
• 5+ years of experience writing complex queries using relational databases
• 5+ years of experience using Microsoft Word and Excel
• Minimum of 1 year of experience with working with large databases (> 1TB)
• Exposure to Teradata, DB2 and Oracle
• Excellent written and verbal communications
• Provide first line support for the business reporting tool - IntelliVUE
• Design and implementation of strategic reporting and analysis to track operational performance
• Constantly evaluate opportunities to improve MI quality
• Pro-actively seek to improve MI procedures
• Develop reporting in a user friendly format that supports the business and Operations
• Ensure the quality of MI is excellent and that it is reliable and can be produced consistently
• Prepare and maintain detailed documentation for all processes to agreed standards
• Identify areas within the MI development and production environments where efficiency savings can be made
• Provide analytical support across Operations and/or specific functional business units
• Contribute to strategic business initiatives across Operations by providing performance analysis to support strategies
• Identify the needs of the customer, design and produce new reports, analyse and improve existing reports to both internal and external customers
• Proactively manage customer expectations and requirements ensuring that management information and analysis needs are met to agreed timescales and standards of accuracy
• Act as a consultant to both internal and external customers on behalf of the team and represent the MI team to obtain requirements and report back to Operational management
• Involvement in the analysis that takes place around contract variance work
• Work with Bid Proposal Team, Business Solutions and all Operational stakeholders to ensure all Operational impact is factored into bid proposals and cost models
• Be involved in the planning and implementation of new clients and the development of existing clients within all areas of Operations
• Self-motivating with the ability to work with initiative
• Complex problem solving skills
• Analytical skills with the ability to research and extract information
• Highly influential with excellent conflict management skills
• At least 2 years’ experience within a similar role
• Analytical qualification preferably at degree level
• The ability to work to stretching targets and deadlines
• A keen attention to detail and strong organisational skills
• A demonstrated ability to communicate clearly and concisely with both oral and written forms
• Ability to operate within the team concept effectively and foster a unified team spirit along with the ability to work alone
• Be apprised of technologies and tools available
• Continual professional development
• Experience in a programming discipline, and the ability to read and understand Microsoft SQL server
• Knowledge of Pearson VUE and systems
• Working knowledge of programming methodologies
• Knowledge of SharePoint development
• Knowledge of https. development
• As a senior data analyst you will be able to take full responsibility for all steps of an analytics assignment, from data and business value exploration, data structuring, modelling, problem solving and consulting & recommendation
• You will support the Technology Division with your problem solving and data mining skills, in particular to support product quality improvements and warranty cost performance
• You will develop & implement methodologies to assist project leaders in making forecasts and predictions, e.g. on quality or warranty cost performance of systems, components and vehicle models
• Contribute to process and organizational development in all processes where our analytics tools are used
• Support quality activities in solving processes and Strategic Objectives when applicable
• Bachelor’s Degree in Engineering, Computer Science, Mathematics, Statistics or equivalent required
• Master’s Degree in Engineering, Computer Science, Mathematics, Statistics or equivalent is preferred
• 5 years' experience in data analytics required
• Experience in SAS Institute data analytics tools such as Enterprise Guide, visual analytics, data mining, or data analytics tools from other vendors than SAS are considered a merit
• Multinational company experience is a plus
• 5 years’ of automotive industry experience is considered as merit
• For Sr level a minimum of 4 years analytical work experience in a professional setting
• Thorough understanding of business processes and systems knowledge
• Database experience including the ability to create PowerPoint graphs, tables and information reports in slide format
• Ability to prepare reports and conduct presentations
• Collaborate with internal/external stakeholders to manage data logistics – including data specifications, transfers, structures, and rules
• Provide proficient problem solving and data analysis, derived from programming and marketing/business experience
• Proficient with toolsets (SAS, SAS ODS, SAS Access, SQL, Unix, MS Office) and large datasets
• Document and articulate the steps taken in an analysis
• Answer questions about data sets and analyses
• Provide quality (QA/QC) analysis and related output
• Take a proactive, independent role in project design, planning & execution
• Effectively manage time and resources in order to deliver on time
• Serve as project manager on analyses of limited scope, complexity
• Prepare basic report content (Word, Excel, PowerPoint) including writing covering methodology and findings
• Participate in presentation of results to key internal and external stakeholders, effectively communicating the key findings and recommendations
• Bachelor or Master’s degree in a quantitative discipline (e.g., Statistics, Economics, Mathematics, etc.)
• Minimum 2 years of experience in marketing analytics field
• Some positions require a minimum of 2 years of experience conducting digital analytics
• Proficient in SAS/SQL programming; minimum 3 years of experience
• Strong analytic thought process and ability to synthesize and interpret findings
• Acute attention to detail (QA/QC)
• Proficient in MS Office, including PowerPoint, Word, Excel and Outlook
• Solid planning, priority setting, and project management skills with experience managing multiple projects concurrently
• Successful developing relationships within and across functional teams
• Highly motivated and collaborative team player with strong interpersonal skills
• Contributes to the development of project plans
• Pushes for continuous improvement in process and technology
• Develop frameworks that are used by multiple teams and applications
• Must have experience in agile delivery within data management & analytics
• Work with scrum masters and directors to define solution architecture, work tasks and estimates that will feed into the overall project schedule
• Data platform will be developed using the modern data technologies including Hadoop, AWS, data pipeline using open source stack, Informatica big data edition
• Apply data knowledge and critical/creative thinking skills to collect, transform, validate, and analyze data; design data processes and solutions
• Bachelors or Master’s Degree in technical or business discipline or related experience required
• Typically 3+ Years of experience in coding in data management, data warehousing or unstructured data environments
• Knowledge of big data concepts, strategies, and methodologies; thorough knowledge of business functions and operations, objectives and strategies
• Knowledge of insurance data and metrics with strong skills in logic and pattern recognition
• Experience with database design, data model development, query languages, and ETL process
• Leads in the evaluation of complex business requirements
• Transforms client requests into project data deliverables to include data models, target data mappings and data transformation rules
• Contributes to the development of project plans for data deliverables
• Depicts complex ideas, issues and data designs to varied audiences; communicates project data objectives, scope and direction to project team
• Contributes to data standards best practices. Communicates standards to development stakeholders
• Supports development team throughout project lifecycle, including during test phase; researches test issues and data content, and assists with complex problem resolution
• Investigates new tools and techniques; collaborates on hardware/software evaluations
• Bachelors or Master's degree in a technical or business discipline or equivalent expertise. Generally a minimum of 5 years related experience
• Extensive knowledge in the following areas; IT concepts, strategies and methodologies, IT architectures and data standards, data design and tools and business function(s) and of business operations
• Proficiency in SQL and DBMS languages and tools and new and emerging technologies
• Effective negotiation, facilitation and consensus building skills and strong communication and presentation skills
• Familiar with Big Data concepts, in addition, exposure to technologies such as Hadoop / MapReduce
• Some exposure to a statistical package or language (SAS, R, etc.)
• Primary team member responsible for gathering and deploying financial and customer data into analytical tools and data solutions to enable growth, drive profitability, and improve process efficiency
• Cleansing, blending, and providing data needs for the Project Management and Finance teams
• Updating, improving data integrity, data mining, and statistical analysis of transactional sales databases
• Utilize programming skills to synchronize multiple data inputs into a clean, user friendly output across various business platforms
• Coach, mentor, and raise the overall acumen and effectiveness of the team in data management, blending, analytics, and insights
• Support system and technical improvements, partnering with technical teams to improve data integrity and availability
• Drive and continually improve upon analytical processes used to understand the performance of the business
• Ad hoc analysis and special projects as requested by Project Management Team Leader
• Bachelor’s Degree in related discipline to include but not limited to: Statistics, Mathematics, Economics, Finance, Marketing, Computer Science, Information Systems, and Analytics
• 5+ years of experience in cleansing, blending, analyzing, and visualizing data for decision support purposes. Experience with statistical analysis, programming tools, and finance a plus
• Ability to explain technical information to non-technical individuals
• Expert level proficiency in MS Excel, Access, Structured Query Language (i.e., pivot tables, macros, charts, creating queries, and downloading data from existing queries.) Macro and VBA development a plus
• Working knowledge of Siebel, Oracle, and SAP databases is preferred
• Leverages appropriate technologies to support analytic needs of division
• Architects, designs and builds data solutions leveraging database and reporting tools
• Consults and collaborates on assessment activities
• Uses statistical methods to analyze data and generate useful reports
• Provides business analysis to identify and recommend ways to streamline business processes; and
• Provides support to system data integrations
• Bachelor’s degree or equivalent combination of education and experience
• Significant experience in a data analyst or data developer role
• Proficiency in writing SQL with enterprise database platforms such as Oracle or SQL Server
• Demonstrated experience with enterprise reporting platforms
• Demonstrated experience in database design experience
• Demonstrated experience in scripting involving data integrations
• Demonstrated experience working as part of a team; and
• Master’s degree
• Experience working with predictive analytics tools; and
• Experience working within student affairs higher education environment
• Works directly with Optum Payment Integrity Practice and their customers to define project requirements, provide assistance in delivery of data, and to answer questions related to project results
• Analyzes customer claims data to ensure that content provided will support scope of projects to be delivered
• Transforms and loads customer data in SQL Server environment
• Processes data according to project specifications
• Organizes and communicates results to customers in the form of data sets, reports and/or presentations
• Devises analytic methodologies to deliver creative and meaningful results for our customers
• May engage in the development of new products and solutions to enhance revenue growth opportunities
• Bring your talent to an industry leader with the information, technology, and consulting expertise to help transform health and human services. No matter what your role, you'll be empowered to ask more questions, develop better solutions and help make the health care system greater than ever
• 2+ years health care data, mainly UB and HCFA claim content experience. Must be familiar with claim structure data components and relationships
• 3+ years developing complex SQL queries and scripts
• 2+ years’ experience performing Data Extraction, Transformation and Loading (ETL) of data in an SQL Server environment
• 2+ years plus SSIS experience
• Experience with data editing tools such as UltraEdit
• Excellent data quality assessment skills. Must be able to leverage knowledge of UB and HCFA claims to quickly identify problems within a submitted claims dataset
• Excellent data analysis skills and a demonstrated ability to assess patterns, trends and behaviors within large health care claims populations
• Excellent data presentation skills. Must be able to develop formatted reports using MS Office tools that are presentable to customers (mainly Excel, PowerPoint and Word)
• Experience pricing Medicare facility claims (inpatient and outpatient)
• Knowledge of PPS payment systems and methodologies
• Support development and implementation of quality and warranty analytics strategies and roadmaps
• Participate in strategic projects and coordinate actions to support the achievement of defined objectives
• Improve operational excellence
• Solve complex challenges in areas of data mining and optimization
• Support the solving of urgent quality issues with advanced analytics
• Visualize data in an appropriate format
• Develops and deploys reporting and analysis that is accurate, complete and properly summarized to aid in management of business and management decision making. Responsible for extracting and summarizing data from JDE and other corporate systems
• Has expert knowledge of JDE tables and field usage. Has thorough knowledge of other corporate software, programs and data tools. Assists managers with report design and development. Tests reports and ensures that they perform as expected
• Produces weekly, monthly, and quarterly trend and activity reports as well as other operational and management reports. Ensures that reports are produced per scheduled timelines for review by functional management teams
• Analyzes large amounts of data and investigates and researches anomalies. Works with department and/or functional teams to correct issues when identified
• Produces ad-hoc reporting as assigned
• Relational database experience
• Knowledge of a database coding language such as SQL, preferred
• Excellent PC skills –advanced Excel functions
• Ability to summarize large amounts of complex data into management reports
• Ability to problem solve to determine root causes of anomalies
• Responds well under pressure with deadlines
• Translate real-world, abstract business questions into business models that identity patterns and trends and provide business insight
• Work with Enterprise Accounts, Contract Operations, Marketing, Finance and other key stakeholders and subject matter experts to define business objectives and identify and obtain data to support business models
• Analyze and synthesize raw data sets into meaningful insight
• Influence business decisions by creatively visualizing and reporting findings so that the data tells an impactful story
• Ensures master data integrity in key systems as well as maintaining the processes to support the data quality
• Identifies areas for data quality improvements and helps to resolve data quality problems through the appropriate choice of error detection and correction, process control and improvement, or process design strategies
• Ensures quality of master data in key systems, as well as, development and documentation of processes with other functional data owners to support ongoing maintenance and data integrity
• In collaboration with subject matter experts and data stewards, defines and implements data strategy, policies, controls, and programs to ensure the enterprise data is accurate, complete and reliable
• Provides assistance in resolving data quality problems through the appropriate choice of error detection and correction, process control and improvement, or process design strategies collaborating with subject matter experts (SMEs) and data stewards
• Manages, analyzes, and resolves data initiative issues and manages revisions needed to best meet internal and customer requirements while adhering to published data standards
• Work closely with the business/IT to ensure alignment of master data rules and the operations of the application meet all requirements
• Bachelor’s degree in information science, data management or related field or equivalent combination of education and experience
• 5-7 years working experience in the medical device or healthcare industry with strong analytical and problem-solving skills
• Strong business acumen with the ability to translate information into relevant and actionable insights
• Related work experience with data warehouse and business intelligence tools
• Excellent knowledge of Microsoft Office using Excel, Access
• Excellent knowledge of Tableau
• Comfortable working in newly forming, ambiguous areas where learning and adaptability are key skills
• Outstanding communication and interpersonal skills
• Ability to deliver high quality work in a fast-paced environment
• Ability to mentor others
• Intellectually rigorous, analytical, and curious
• Dynamic, motivated, resourceful, and results-oriented creative thinker and problem solver
• You are responsible for design and implementation of innovative technologies and algorithms from an idea to a software system
• You have the responsibility for the technical leadership/coordination of the the Data Analysts group
• You analyze and identify new data related business opportunities in the manufacturing area (Internet of Things)
• You take over the development of complex algorithms utilizing modern approaches from the domains of machine learning and advanced data analytics in general
• The interpretation and analysis of data from complex technical systems belongs to your tasks
• You identify new technological advances and develop of own invention disclosures
• You coordinate and execute (sub) projects and take over the leadership of a team of experts
• You have a PhD degree in computer science, bioinformatics, mathematics, physics, or engineering sciences (thesis in the field of Machine Learning and especially Deep Learning is a plus)
• You have longterm expertise and experience with technologies, algorithms and methodologies in the areas of Data analytics and Machine Learning is a must; experience with Deep Learning is welcome (publication record is a plus)
• You have experience with project work in the research and development area especially in the domain of data discovery and data science is highly appreciated
• You have knowledge of and experience with modern analytical frameworks, libraries and analytical development frameworks
• You also have knowledge of software development process and good programming skills in particular Python and Java combined with knowledge of analytical libraries. Agile experience is a plus
• You have experience with massive parallel processing (Hadoop, Spark) and stream analytics (Storm, Spark Streaming) as well as relational databases is appreciated
• You have advanced speaking and writing skills in English (German is a plus)
• 10+ years of experience relevant to this position including 5 years of consulting experience. Management or team leadership experience preferred. Undergraduate degree or equivalent experience preferred. Product or technical expertise relevant to practice focus. Ability to lead large teams. Strong influencing and negotiation skills. Ability to travel as needed
• 7+ years proven experience using your digital knowledge to sell new client engagement and expand existing engagements
• 7+ years deep experience in interactive marketing - email marketing, social media, website analytics, search marketing, online acquisition, mobile marketing, display marketing
• Experience and success managing projects with multiple team members, ensuring quality work on existing client projects
• Inter-Services/Team Communications: Ability to work with other teams to ensure client success, and also develop work with those teams to educate and learn for future opportunities
• 5+ years working in an agency or consulting firm
• Hands-on skills using data to drive decisions – proficiency in Excel is required
• Experience translating data analysis into actionable marketing recommendations and presentations – proficiency in PowerPoint is required
• Oracle Platform Knowledge: Knowledge of key Oracle Marketing Cloud technology platforms and their capabilities is desired (i.e. Responsys Interact, Eloqua, BlueKai and Maxymiser) in ensuring the right strategies are using the right technology to deliver results
• Ability to leverage business experience / acumen to identify new business and marketing opportunities
• Excellent verbal and written communication skills along with project management and interpersonal communication abilities (ability to produce professional reports and present to senior-level executives within client organizations.)
• Strong listening and superior relationship building skills
• Outstanding attention to detail and high personal quality expectations
• High intellectual curiosity, drive, determination, self-confidence and persuasion skills
• Self-directed and self-motivated with a demonstrated work ethic and ability to perform under pressure and meet deadlines
• 40-50% travel required
• Bachelor’s Degree required, Advanced Degree strongly preferred (preferably in Marketing, Business Management, Economics, Statistics or other related coursework)
• Interpret data, analyze results and provide ongoing on-line reporting
• Work with your manager and teams to prioritize business and information needs
• Look for process improvement opportunities
• The ability to work independently or as part of a team
• The desire to mine data and develop solutions
• MS/MA in Data Analytics, Data Science, Computer Science, Information Management or other Engineering Discipline
• At least 10 years of experience in a data analyst or similar position
• Knowledge of relational database systems
• Experience with Data Analytic Tools
• Assist in implementing core Data Governance disciplines including but not limited to
• 7+ years of experience in analysis, mappings, modeling, designing and implementing quality data management solutions working closely with key business stakeholders
• Experience with SQL development, SSIS and similar, related technologies is a plus
• Experienced in working on data management across transactional and analytical processes preferably in a global company with users across multiple business units
• Experience implementing tools (preferably Informatica) for data management including Metadata Management (Business Glossary and Lineage), Master Data Management, profiling, cleansing, modeling (Erwin), Business Intelligence etc
• Generally a minimum of 7 years related experience. In-depth knowledge of IT concepts, strategies and methodologies
• Must be proactive, and have the ability to work independently/efficiently and to thrive in a fast paced environment, as well as the ability to work collaboratively with cross-functional teams
• Acquire data from multiple data sources for analysis
• Identify, analyze and interpret trends or patterns in complex data systems using appropriate statistical and data mining techniques
• Help with the analysis of usage patterns of our websites. Actively contribute to finding new methods to understand user behavior and areas of struggle in their online experience
• Present data findings to senior management
• Support day to day data requests as required
• Test and audit the quality of data collected and work with the development teams to correct any inaccuracies/inconsistencies
• Coordinate with other team members to ensure timely execution of the project plan
• Technical expertise regarding data models, database design, data mining and segmentation techniques
• Strong knowledge of statistics and experience using statistical packages for analysis of large datasets (Excel, SPSS, SAS, R, etc)
• Familiarity with metrics used in email and web analytics
• Strong interpersonal skills to build effective business relationships
• Ability to work in a fast paced environment with ever-changing deadlines
• 5 years demonstrated experience in the Technology/IT industry
• 5 years demonstrated experience as a Data Analyst
• Master’s degree in Mathematics, Computer Science or related field
• Experience with Adobe Analytics (Omniture) Toolset
• Experience with Microstrategy
• Detailed understanding of web analytics concepts and principles
• Experience with complex, multi-national application implementations
• Lead the planning of projects for the development of new data analysis algorithms, reports, database structure, and workflows
• Provide direction to data analysis staff and ongoing development, support and training as needed
• Perform complex queries and data mining methodologies to identify patterns and trends that are indicative of potential fraud, waste, and abuse using traditional as well as predictive/advanced analytic methodologies
• Conduct quality assurance reviews on data analysts’ work
• Develop specifications and extract data for data requests from all data sources, including, but not limited to the CMS Data Engine (a SAS environment) claim system
• Provide ongoing data analysis support as needed, including the development of scripts, algorithms, views, tables, databases, and spreadsheets
• Conduct quality assurance reviews of data loaded into HMS Federal’s data repositories to ensure data loads are complete, accurate and conform to business requirements, this Includes reviews of work conducted by subcontractors and internal staff
• Interface directly with customers and stakeholders to provide analytical support
• Analytical ability and business acumen to collect multiple sources of data and draw conclusions
• Ability to learn new tools with minimum guidance and work independently
• Mastery of spreadsheets and analytical tools including Microsoft Excel and Microsoft Access
• Demonstrated ability to meet and exceed project deadlines while producing high quality products
• Knowledge of health care information (e.g., health claims data specifically Medicare and Medicaid), ICD-9/10-CM codes, and physician specialty codes)
• Working knowledge with the Centers of Medicare and Medicaid Services (CMS) Integrated Data Repository (IDR), One Program Integrity (One PI), Shared Systems, and/or Common Working File (CFW), and other fraud detection and prevention solutions
• Working knowledge with state Medicaid claims and systems such as Medicaid Management Information System (MMIS) or Medicaid and Statistical Information System (MSIS)
• Understanding of applicable regulations as they apply to the Provider type and the review as well as the contract requirements for business engagements
• Knowledge of HIPAA Privacy and Security Rules and CMS security requirements
• Certified Fraud Examiner (CFE), Accredited Health Care Fraud Investigator (AHFI) – Preferred
• Not currently sanctioned or excluded from any program operated by Federal or State Agencies including Medicare and Medicaid - Required
• 5+ years of related data analysis experience including at least 3 years recent experience with Medicaid claims data and/or Medicare Part A, B,DME and Home Health claims data
• Including 5+ years’ experience with SAS, Microsoft SQL, Business Objects or Crystal reporting
• Proactively identify opportunities where data collection and analysis can improve business processes and influence decisions
• Interface with technical and business teams to collect/extract data from various data sources (in-house databases, machine logs, third party vendors, and others)
• Work closely with these teams to assure that needs are understood, and requirements are defined and met
• Assist Data Scientists in the exploration and validation of data, including understanding and championing the business point of view
• Partner with the functional business areas to understand their needs then define and develop methods to present analytical findings - including, but not limited to, dashboards, reports, and summaries
• Present findings of analyses in non-technical terms to facilitate understanding by a wide audience
• Satisfy ad hoc data requests while working with the team to design a self-service system, minimizing the need for these requests
• Participate in quality checks on the completeness and accuracy of data, working with end users to follow through on associated action items
• Leverage data to drive the strategic direction of the organization
• Attend vendor training and/or conferences and presentations for continuing skills development
• Train and mentor team members and other DeVry colleagues as necessary
• A Bachelor’s Degree is required - preferably in math, economics, engineering, statistics, information technology or a similar technical field
• Minimum of five (5) years of experience performing business data analysis with a deep understanding of how data can drive business decisions and success
• Strong analytical, communication and documentation skills
• Ability to present complicated information in understandable terms with a strong grasp of both technical and business perspectives
• Strong critical thinking, as well as organizational, multi-tasking, prioritization and interpersonal communication skills
• Ability to interact with all levels of the organization and work in a fast-paced environment
• Ability to work independently and make sound decisions with minimal supervision and direction
• Strong sense of ownership and driving resolutions to projects
• Solid SQL skills and an understanding of database structures to perform research and discovery
• Experience with data visualization tools (Tableau, Qlik, Microsoft Power BI, SAS, Birst, Cognos, others). Significant experience is desired
• Experience with strategic analytics tools is a plus (R, SAS, others)
• Assist in evaluating the effect of payor reimbursement trends and system modifications
• Provide day-to-day system support for Patient Financial Services (PFS) staff and must be able to assist in identifying root causes
• Generate financial and statistical reports, obtaining data from disparate sources after determining the applicability and accuracy of the information
• Re-evaluate system functionality and staff usage and assists in identifying opportunities for improved efficiency through better processes and additional automation
• Execute components of special projects as assigned; may be responsible for coordinating activities with others in the department to produce reports and other deliverables within the prescribed timeframes
• Generate concise, timely reports of departmental activities and/or variances from expected results
• Analyze master files, profiles, and table changes to ensure all changes are appropriately entered
• Schedule and monitor staffing levels to ensure efficient operations and appropriate employee utilization
• Comply with and adhere to all regulatory compliance areas, policies and procedures (including HIPAA and PCI compliance requirements), and "leading practices" Recruiter will enter
• Working with Tableau and SQL
• Concept and perform strategic data analysis and research within SAP systems and / or with dedicated software solutions to support business processes and strategy
• Analysis of unstructured data with text mining procedures and discuss results with Managers
• Translation of requirements, creation of functional specifications, extraction of data and development of SQL scripts
• Preparation of engagements by creating regular status updates for the Engagement Manager and independently determining the engagement requirements prior to fieldwork
• Partial project responsibility and full Reporting to Engagement Manager
• Preparation of presentations for final review of all documents and active participations at closing meetings with management
• Creation of Use Cases for Siemens internal pre-sales and sales process
• Conception and creation of reference projects and presentation of those during management and internal client meetings
• At least 3-4 years of professional experience within Siemens, a related industry, a ‘Big 4’ accounting firm or a global strategy / IT consulting firm
• Strong academic history (Master’s degree in IT or business related fields)
• At least 2 years experience with SAP modules (PP, SD, MM, PS, FI or CO) and/or statistical data analytics (R, SAS, Matlab, etc.) or process mining technologies
• Experience with visualization of complex data (e.g. QlikView)
• First experience with managing data projects
• Very good knowledge of MS Office
• Desire and drive for future leadership roles
• Fluent in English and willingness to travel 70% - 80% of your time globally
• Data Analysis: Performing data analysis for small to medium-sized projects, including working with business partners and leaders, and technical staff to prepare outputs that align with customer expectations
• Managing the Open Data Program: Ensuring open data is extracted from source systems, vetted against a checklist for public posting, updated to improve data quality and usability, loaded into the client's data hub, continuously maintained, and secured
• Developing Open Data Standards and Processes: Applying industry standards and best practices for data and metadata collection and management, and developing processes to ensure each data requests and/or new data sources are appropriately reviewed, posted and maintained
• Assist in incident review to identify alerting trends, establish CTI and other documentation standards to better identify problem areas specific to SBI systems and applications
• Exercises good judgment within defined procedures and practices to determine appropriate action. Demonstrates the ability to effectively prioritize tasks with limited direction and seeks assistance when appropriate
• Shows the ability to gather specifications, understand and define the problem, and identify and evaluate potential solutions to the problem. Ability to see commonality in a problem set to develop a generic solution, which can be extended to solve multiple problems
• Assist stakeholders and project leaders with negotiating and prioritizing requirements
• Assist in the identification and implementation of process improvements and designs, which result in measurable improvement to customer experience and operations performance
• Exhibits a detailed understanding of our information systems and their relationship with SBI business processes
• Collaborate with SBI teams to communicate and validate the adoption of process changes
• Ensure that new processes are documented and that changes are communicated to all affected parties
• Has a technical understanding of data center and server architecture within it
• Award-winning education and training across multiple career paths to help you reach your potential
• Bachelor of Science in Computer Science, Information Technology, Software Engineering, Technical Writing, or appropriate combination of education and experience in Essential Duties and Responsibilities
• Advanced computer skills and proficiency with MS Word, Excel, PowerPoint, Project and Outlook
• 4 – 6 Years of Enterprise Experience in a server environment
• Minimum of 2 years’ experience developing SOP/procedural documentation, requirements/design documentation, test, qualification and validation plans and documentation
• Technical certifications such as MCSE and non-technical certifications such as ITIL Foundations a plus
• Commitment to DaVita’s values of Service Excellence, Integrity, Team, Continuous Improvement, Accountability, Fulfillment and Fun with ability to demonstrate those positively and proactively to patients, teammates, management, physicians, and/or vendors (Village Service Partners) in everyday performance and interactions
• Strong analytical skills with the ability to seek out underlying assumptions through probing, questioning, and listening
• Minimum of 4 – 6 years previous experience in an Analyst or equivalent role
• Ability to work within deadlines and with multiple priorities; ability to adapt to changing priorities
• Well-developed time management skills with the ability to respond to urgent requests in a timely manner
• Demonstrated ability to work in a team, facilitate effective team interactions, and to foster a positive work environment; willingness to assist teammates in order to achieve departmental goals
• Strong written, verbal, and interpersonal communications skills including ability to listen attentively and to communicate information clearly and effectively
• Primary team member responsible for gathering and deploying financial and customer data into analytical tools and data solutions to enable growth, drive profitability, and improve cash flow
• Develop and prepare timely interpretive reporting, analysis, trends, and forecasts to meet channel requirements
• Analysis of budgets, forecasts, trends, and recommendations of corrective actions/focus areas to address performance issues
• Drive and continually improve upon financial processes used to understand the performance of the business
• Partner with, but not limited to, Regional Directors, Sales Leaders, Services Operations, Finance, Credit teams and Customer Center District Leadership
• Assist in the rolling forecast, target setting, and annual planning process
• Assist with the monthly close process, ensuring accurate and timely financial results with the ability to drive process improvement
• Ad hoc analysis and special projects as requested by Management
• Cleansing, blending, and providing data needs for the Sales Channels, Finance, Marketing, and Services Teams
• Process data from Active Readiness Information System (ARIS), online Billet Change Request (BCR), the Total Force Manpower Management System (TFMMS), TFMMS Web Online, and Fleet Training Management Planning System (FLTMPS) to support the manpower requirements
• Review and maintain accurate manning data contained in Officer Distribution Control Report (ODCRs) and Enlisted Distribution and Verification Reports (EDVRs)
• Responsible for working with a team in the technical planning and design for the network
• Responsible for the development and validation testing for network design and integration
• Maintain databases to generate the Long Range Training and Replacement Plan (LORTARP) and other Manpower and Personnel management documents and reports
• Maintain billet assignment data and producing and distributing reports, review and analysis
• Create/maintain/update the Position Mapping database
• Provide support for data input and analysis of CSCS Domain’s Position Mapping files
• Use Corporate Enterprise Training Activity Resource System (CeTARS) and AMD data to update Position Mapping files and instructions, analyze data, report data, and make recommendations for changes to manpower based on their findings
• Identify, collect and analyze data; perform trend analysis and identify problems/areas of opportunity
• Bachelor’s degree in related field and 4 – 8 years of experience
• Five 5 years’ experience in reviewing, updating and evaluating Navy Training Management corporate database systems such as CeTARS and FLTMPS
• As a data analyst you are responsible for the creation of analysis models based on data from different sources and in different formats
• You coordinate work with other departments, partner firms, and suppliers
• You will take over the responsibility for planning, conception and implementation of new data-based solutions and their interfaces
• You will analyze new components and methods, and pilot solutions in order to implement initial “proof of concepts”
• You will gain good business understanding through analyzing data with a focus on the perspective of “Imaging / Radiology” customers&#8217
• You share responsibility for the quality of the products and services, and take care of the documentation of the projects and their budgets
• You will work on a strategic development project in close cooperation with the collaborating business lines/areas
• You hold a university degree in the field of information technology, mathematics, or economics. Alternatively, you have completed a professional training and have several years of experience in these fields
• You have several years of professional experience in the field of data analysis and visualization, preferably within the Healthcare industry
• You have sound technological expertise with the following products: Microsoft Azure/Hadoop, XMART, SAS, Rapidminer, QlikView, and/or SPSS
• You have excellent written and verbal communication skills in English and German
• You have keen abilities with problem solving and de-escalation, as well as the ability to work with others, and you interact well with colleagues during implementation
• You have good persuasion and communication skills, customer orientation, target orientation and analytical abilities, as well as a structured work ethic
• Provide data mining and analysis to support various CBU initiatives and assist in Wireless revenue and usage inquiries
• Provide standard reporting support, which includes the ability to extract and analyze large and complex data sets from various source systems and data stores by performing coding and system parameter setting
• Responsible for writing queries, filtering and transforming data into meaningful reports for Financial analysis and Pricing, Commercial strategy and Sales teams
• Process and analyze data to support business case analysis and ad-hoc requests. Define data requirements and ensure accuracy of data pulls
• Perform ad-hoc queries and develop / automate financial / statistical models using a variety of software applications (Excel, MS Access, SAS/SQL); provide recommendations and insights
• Investigate and help resolve possible data corruption and discrepancies
• Liaise with IT to understand best sources of data and tables
• Lead special projects / ad-hoc assignments as required
• University degree in Computer science, Mathematics or related field
• 3+ years programming skills with advanced knowledge of SAS, SQL, data mining software and Excel Macros
• 3+ years experience in DBMS
• The ability to construct datasets, ensure data quality and perform quantitative / basic statistical analysis
• Excellent knowledge of Microsoft Office and strong ability to learn new software
• Excellent organization and time management skills to meet deadlines and handle changing priorities
• Minimum 5 years of data analysis experience
• Must be able to write complex SQL queries
• Need experience working in a large, complex commercial environment
• Highly motivated, results driven, and challenge oriented individual·
• Strong analytical problem solving and data analysis skills, with attention to detail
• Creative thinker with ability to provide solutions to complex challenges/opportunities and as part of a team
• We need a self-starter who can work independently
• Any experience with a CRM-System is helpful
• Experience working with an ETL tool like Informatica
• Experience with VBA or R is helpful (or another programming language)
• Consulting experience
• Expected to help the CA team achieve its targets for billable hours, revenue, and operating margin
• Responsible for regular project documentation in accordance with team standards, process, and policy
• Expected to contribute ideas and effort to: the exploration of current, evolving, and future data assets in order to generate novel insights that engage clients and attract prospects; the development, testing, and implementation of analytical tools and processes that can increase efficiency or enhance products and services; and the general success of Optum Life Sciences
• Collaboration with cross-functional teams inside a matrix and geographically dispersed organization
• Provide training, direction, oversight, and quality control for junior staff, which may include analysts located overseas
• Serve as a sounding board or source of education for peers, co-workers, or other stakeholders with an interest in the content, structure, provenance, and potential uses of Optum's health data
• 10+ years of experience with SAS programming in a UNIX and/or PC environment
• 8+ years of experience generating, manipulating, and analyzing complex patient, consumer, customer, or company data
• 4+ years of experience producing or supporting data analysis for clients or other external audiences
• 4+ years of experience training, supervising, evaluating, and mentoring junior staff
• Ability to travel (up to 10%)
• Bachelor's degree in biostatistics, mathematics, computer science, theoretical physics, quantitative social sciences, statistics, or information systems OR technical certification in programming or data processing
• Knowledge of insurance claims data and/or electronic health records
• Experience with the healthcare industry, including biopharma, medical devices, managed care, or hospitals
• Advanced degree (MBA, MS, PhD)
• You must love data. Expert of using data analysis, data visualization and predictive modeling to tell story and solve complex business problems
• Prefer candidates with 2-3 years of work experience in highly analytical role
• Experience with Tableau, SQL, SAS, R
• Highly analytical and creative thinker comfortable working with ambiguity
• Must be self-directed, organized and detail oriented as well as have the ability to multitask and work effectively in a fast paced environment
• Strong team player, excellent communication skills, positive attitude and good work ethic
• Prior experience of supporting global sales team is plus
• Build Sales territory coverage models to analyze, diagnose and present to the management team
• Develop and maintain advanced Sales KPI dashboard to provide insights into business
• Provide in-depth Go-to-market analysis from sales perspective to drive the alignment between Sales and Marketing
• Proactively diagnose the analytical requirements of the sales organizations; design and deliver reporting to meet their requirements
• Manage and maintain existing Excel based analytics and transition to Business Intelligence platform
• Maintain data quality and business process documentation
• Actively offer suggestions on refining sales processes, analysis, and related activities to automate systems and processes
• Working with the Marketing Operations Director/Senior Data Planner to help develop data models for campaigns and future CRM development
• Develop and build a variety of reports for the client, primarily using SAS, Excel and Adobe, but also with other software packages as directed
• Build, validate and deliver specific analytic models designed to generate true customer insight
• Develop and provide written and verbal output on reports
• Manage and resolve the key data strategy issues involving quality, consistency and growth across customer and prospecting database in consultation with colleagues
• Develop the data models across the Customer Journey from acquisition through to repurchase including insight based campaign targeting strategy
• Drive campaign optimization by establishing and managing the test and learn process for campaign reporting
• Convert analysis output into customer insight that drives marketing performance
• Briefing external suppliers and internal marketing operation functions, as required
• Build relationships with management and staff (internal & external) in business areas associated with data planning work
• Understanding of digital marketing, customer relationship management, eCRM, and programmatic campaign management
• Bachelor’s Degree in Mathematics, Statistics, Marketing, Economics, Computer Science, Information technology or Human-Computer Interaction or related discipline
• Three to five years’ experience in marketing or business analytics setting and statistical analysis, predictive modelling an advantage
• Digital media as an optional requirement
• Ability to document complex data sets and calculations and ensure products meet standard best-practices and appropriately model a scenario. Ability to use those documents to test and validate the integrity of data-driven products
• Ability to create new methodologies for clients around goal-based planning, Monte Carlo simulations, financial modeling and multiple outcome scenarios
• Help to drive and suggest new innovations and technologies for our data-driven products, including ways to improve charting, speed up calculations, and ensure flexibility in data modeling
• Work closely with the product and technology teams in the development of new products. This includes helping to determine the best ways to store data, update it and ensure a flexibility product set for our clients
• 3 years data modeling or other data or object-related work experience demonstrating knowledge of database management systems and data management tools
• Be the in-house data expert - with in-depth knowledge of fund reporting data. Will be a key resource for the editorial and development teams in the creation of new financial content and products
• Ability to create test plans, programs, and/or excel documents to validate calculations and data
• Ability to write technical documentation explaining the algorithms and logic needed for technology to build calculation engines
• Ability to document and validate new and existing methodologies for regulatory review and submission, as well as passing review by clients subject matter experts and compliance and legal teams
• Using advanced quantitative and analytic skills, respond to requests for data, including sourcing it, creating charts/tables, as appropriate, and analyzing and interpreting complex data sets
• Be able to explain complex statistical concepts in a way that non-technical individuals can understand
• Report on project status, estimate work requirements, all while managing a variety of distinct initiatives
• Exceptional Excel skills, advanced SAS software skills including basic data functions and macros
• BS in Statistics or Mathematics. Experience working within the financial services industry – experience across equity, fixed income and packaged investment product is a must
• Must be a CFA
• Be the company's data expert and be naturally passionate about helping others leverage and understand data and the power of statistical methods
• Background in programming, VB macros or other technologies to help the technology team build calculation engines
• Candidate must possess at least a Bachelor's/College Degree in any field
• Required skill(s): Data Analysis, Data Management and Administration, Report Generation, MS Excel, Systems/Tools (examples: Taleo, Salesforce, Oracle, SAP, PeopleSoft, HRIS,web management system/tools, internal systems, etc.)
• One to two years of working experience, preferably in a multinational corporation or shared services environment
• Must have excellent oral and written English communication skills
• Must have strong customer service orientation, ability to work well under pressure, good independent judgment, high attention to detail
• Must be a proactive problem solver who is effective and efficient in the administrative process and comfortable speaking and collaborating with different cultures and nationalities
• Experience or exposure to the Apache Hadoop distribution of tools and associated products; typically, Hive, Pig, HCatalog and Map-Reduce procedural programming languages
• Use data analysis, basic / descriptive statistics, and data exploration techniques
• Identify areas for improvement or optimisation that are actionable and can deliver a return on investment
• Use data analysis techniques to deliver quick working prototypes to prove hypothesis by building statistical models using a range of tools including R, Python, and Spark
• Using algorithms to help deliver data products and work with the software engineering team to correctly embed these algorithms in our British Gas and Centrica platforms and products
• Use cutting edge visualisations to enable our business to better explore the patterns and trends hidden within our data
• Actively promotes best practise and knowledge sharing of data analysis techniques both within the data science team and with external stakeholders
• Owning and guarding data templates for legacy system transfer to the new Infor cloud M3 System, the data mapping required, it’s sequencing and integrity to other data domains to support successful migration to Infor M3 Core Systems and its functional and reporting/BI capabilities
• In the medium term, to investigate and document the possible usage of an Extract, Transform and Load (ETL or ETL lite) toolkit to prepare data in a staging area
• Identify Pricing data improvement with specific business leadership alongside the TP Data Lead in order to minimise data inconsistencies, identify any causes and work with the Data Analyst of each Legacy systems team to rectify as appropriate
• Support the development of Infor M3 system Data Quality rule sets alongside the data quality resource made available to the Data team. This is to be deployed as an approval’s gate to loading into Infor M3’s various target systems
• Degree in Information Systems or equivalent
• 5 or more years of experience developing business intelligence reports
• Experience with financial databases
• Expert with SQL Server Reporting Services
• Expert with SQL Server T-SQL
• Proficient with SQL Server SSIS packages
• Good Oral & Written Communication Skills
• Track record of keeping up-to-date with technologies
• Experience working on an Agile SCRUM team (preferred)
• Must be able to function as part of a team
• MCSE: Business Intelligence Solutions Expert (Advantageous)
• Data gathering
• Innovative & Energetic
• Proactive & Capable
• Easily Approachable
• Apply critical thinking to quickly identify and resolve data issues
• Inspect and cleanse data for accuracy and quality
• Consolidate and summarize data for business partners
• Develop merchant facing ROI, marketing and campaign dashboards
• Organize data and supporting information into visual representation of data analytics to highlight information and trends based on data provided
• Perform statistical analysis (correlation, regression, or time series) analytics
• Support finanancial analysis
• Identify and summarize trends based on data analysis and suggest business improvements based on analysis for both internal and external clients
• Assist with general data and reporting inquiries with a sense of urgency
• Provide assistance with process improvement as needed
• Business stakeholder for providing requirements into reporting and BI products
• Support analysis, monitoring, for franchise settlement product and serve as a subject matter expert for product enhancements and support
• Bachelor’s degree or equivalent; and two to four years related experience and/or training; or equivalent combination of education and experience
• Experience writing MySQL, Bash and VBA
• Excellent organizational and administrative skills, including the ability to organzie, prioritize, and manage simultaneous projects
• Leveraging information to better understand business practices across the Sector
• Proactively identifying and responding to concerns or trouble spots
• Further enhancing our internal control procedures and coverage
• Support the data analytics needs of the Industrial Sector, including
• Understanding of respective objectives and creatively defining analytics that can deliver efficient, effective, and meaningful information
• Gain an understanding of business processes, evaluate potential risks and work with the team and customers to define data indicators of risk
• Partner with individuals in the Sector / Groups and provide analytic services
• Assist in the development and execution of analytic routines while maintaining acceptable cycle time / quality standards
• Provide insight and guidance on the management of reported exceptions / analytic output
• Bachelor’s Degree in Information Systems, Computer Science, Finance, Accounting, Business or Mathematical/Statistical disciplines from an accredited institution required
• Minimum 2 or more years of experience in accounting, auditing, Information Technology, and/or data analytics
• Knowledge of data base structures, data mapping, and experience extracting/analyzing data from common Enterprise Resource Planning (ERP) systems such as Oracle and Mfg/PRO
• Strong knowledge and working experience with data manipulation tools (ex. SQL) to query large databases and manipulate large data files
• Intermediate analytical skills and advanced knowledge of one or more common data analytics tools and CAAT (Computer Assisted Audit Technique) technologies (e.g., ACL, IDEA)
• Adept in using advanced features of MS Access and MS Excel
• Strong attention to detail and an ability to prioritize and work in a highly fluent and fast paced environment
• Apply critical thinking and data analysis skills using ClickFox to develop robust journey insights and recommendations that drive change
• Deliver executive-level presentations that communicate business relevance of the analysis performed and recommended solutions
• Partner with the Customer Experience and Operations teams to create cross-channel dashboards that enable better understanding end-to-end customer journeys
• Deliver strong business results through the successful application of continuous improvement principles across core customer journeys
• Track and communicate the delivery of business value through the transformation
• Establish processes, document methodologies, benchmarks and key learnings for Customer Journey Analytics
• 7-10+ years in hands-on data analytics experience
• 5+ years experience with SAS, R, and/or other data mining tools
• Experience with large transactional databases is preferred
• Familiarity with new big data technologies. (Greenplum, Hadoop)
• Hands-on experience in customer experience analysis, including web analytics, customer segmentation analysis, contact center analysis, marketing analytics, etc
• Proven critical analytical and strategic skills, including the ability to quickly assimilate new information
• Demonstrated relationship management skills with business partners in various lines-of-businesses, operations and IT partners with successful record influencing and leading critical business initiatives
• Excellent communication, presentation and interpersonal skills to convey analytic findings, strategic implications and actionable recommendations to all levels of management and partners
• Ability to present fact-based recommendations in a clear, logical, and concise way; “tell a story” with data
• Master’s or Bachelor's degree with equivalent work experience in Analytics/Business Intelligence fields. (Mathematics, Statistics, or related discipline)
• Development of data infrastructure for enabling processes for lifecycle marketing, search marketing, and other initiatives
• Creation of dashboards and reports providing insight into business data. Monitoring and optimization of existing and new campaigns through data analysis
• Designing and driving and measuring experiments
• Collaborate with team members to gather requirements for analysis and reporting
• Hands-on analysis and manipulation of data to continuously improve conversion and ROI
• Develops data analytics systems to support NGMS objectives
• Utilizes machine learning algorithms, which may include belief networks, Hidden Markov models, Artificial Immune Systems, Gaussian Mixture Models, Decision Tress, graph theory, Information Geometry, Genetic Algorithms, and basic statistical analysis
• Tests algorithms on large and small data sets, including textual, numeric, temporal, and symbolic data
• Employs relevant analytics COTS products
• Programs in Java, JavaScript and/or R
• Collaborates with stakeholders to develop solutions to problems and potential problems
• Interfaces with customers and consumers to develop system requirements
• B.S. degree in a related STEM field, plus a combined 15 years of professional experience in the following areas: Data Analytics systems development, Software Engineering, and Systems Integration
• Demonstrated success developing machine learning algorithms
• Experience using predictive modeling
• Understanding of data storage and retrieval techniques, ETL, and databases– both SQL and NoSQL
• Demonstrated ability programming in Java, JavaScript, and/or R
• Systems engineering knowledge and ability to design data storage and management systems in support of analytics
• Systems integration experience
• Relevant M.S. or Ph.D. Degree
• Ability to incorporate user experience principles for systems and display development
• Systems Engineering experience
• Information Governance experience
• Big Data/data science experience
• User experience and design for systems development
• Ability to obtain a TS/SSBI Clearance, or an active TS/SSBI Clearance
• Master’s degree in Mathematics, Computer Science, Statistics or Related Discipline and 2+ years of related work experience; or a Bachelor’s degree in Mathematics, Computer Science, Statistics or Related Discipline and 4+ years of related work experience; or 6 + years of related work experience
• Data warehousing and distributed computing architectures/applications (Hadoop/Spark/Hive/Kafka)
• Advanced understanding and working knowledge of SQL
• Strong working knowledge of the Property and Casualty industry
• Very strong problem-solving skills, and quantitative/analytical thinking capabilities
• Ability to work collaboratively in a team environment and independently
• Develop partnerships with CITS to provide opportunities for more efficient solutions to various data, system, and applications issues
• Bachelor's Degree or equivalent in Computer Science, Computer Technology or related discipline required
• 5+ yrs business experience
• 3+ yrs related data analytics experience
• Ad hoc prototyping skills using multiple techniques to solve a myriad of business scenarios
• Extensive knowledge of relational databases such as Oracle, SQLServer, and Data Marts and Data Warehouses
• Quick learner, self-motivated and proactive
• Strong attention to detail and acute organizational skills are critical
• 3+ years experience in financial/technical role
• Liaison work
• Familiarity with eLedger / SAP
• Complete data analysis of performance, availability and capacity management metrics in support of ad-hoc and standard reporting requests
• Analyzes and evaluates business outcomes and provides periodic summaries to Customer Experience leadership and all stakeholdersCoordinate internal resources, clients and third parties/vendors for the flawless execution of projects
• Reviews, analyzes, and evaluates business systems and user needs
• Ensure that all projects are delivered on-time, within scope and within budget
• Developing project scopes and objectives, involving all relevant stakeholders and ensuring technical feasibility
• Work along side the technical and operational organizations to optimize Customer Experience, System Quality and Operational Efficiency
• Develop a detailed project plan to track progress and ensure resource availability and allocation
• Develop in-depth awareness and familiarity with issues and events affecting customers
• Communicate and present analysis to a broad audience, including senior managemen
• TDocument requirements and gain consensus across internal and external stakeholder teams
• Present data for validation to clients and internal teams
• Participate in client interactions; review data with clients and statisticians using Excel, PowerPoint, data visualization tools
• Use appropriate verification techniques to manage changes in project scope, schedule and costs
• Measure project performance using appropriate systems, tools and techniques
• Report and escalate to management as needed
• Perform risk management to minimize project risks
• Create and maintain comprehensive project documentation
• At least 3 years of experience in Consulting and client facing roles, business analysis or project administrator
• Bachelor’s degree in administration, management or any related field from an accredited institution is preferred
• Strong clear verbal and written communication and presentation skills is required
• Experience managing and analyzing KPI’s for a customer facing organization
• Excellent interpersonal skills and able to communicate with a wide range of clients
• Excellent analytical, research, numeracy and problem solving skills.Strong decision making skills and the ability to take the lead
• Ability to explain complex information in simple terms and deliver clear and concise client recommendations
• Ability to multitask and leverage escalation procedures.Proficient in PowerPoint for some slide creation and editing
• Proficient in Excel including pivots and reporting as needed
• Experience in Tableau a plus.Certification in Project Management a plus
• Maintain and foster relationships through education and support of data feed processes
• Lead Data Analyst is responsible for end to end data feed task management
• Lead Data Analyst will collaborate between teams and participate in refining processes with managers and/or engineering teams
• Statistical reporting and generation of client metrics
• Solid T-SQL query skills
• Ability to understand a schema and interact with data from highly normalized databases
• Excellent customer service abilities
• Ability to work independently as well as collaborating with management and other teams
• Provide SAS/SQL programming, under general direction, in the execution of data analysis that will contribute to the final project deliverables
• Appropriately account for the timeliness and quality of all assignments
• Collaborate with internal and external stakeholders to manage data logistics - including data transfers, understanding data structures, business rules, etc. - to enable project execution
• QA/QC data and report output to ensure accuracy
• Participate in presentation of reports to key internal and external stakeholders, effectively communicating the key findings and recommendations
• Manage multiple projects concurrently
• Mentor junior staff members
• Assist in the creation of compelling presentations that provide actionable insights and recommendations
• Be exposed to the sales process, providing limited content to be included in proposals for new and existing business opportunities
• Prioritize and monitor project progress relative to timeline and scope
• Bachelor or Master’s degree in a quantitative discipline (statistics, economics, mathematics, marketing analytics)
• Proficient in SAS/SQL; minimum 3 years’ experience
• Successful developing relationships within and across functional teams (including statistical, technical, and marketing resources)
• Highly motivated and collaborative
• Advanced degree (Master’s/PhD) in Statistics, Economics or other quantitative discipline
• Ability to display data visually, creating powerful presentations which effectively demonstrate the value of analytic deliverables; proficiency with business visualization tools (e.g., interactive dashboard software)
• Ability to program in newer and emerging languages such as R and Python; working knowledge of Hadoop and other big data technologies
• Minimum education requirement of four year degree in statistics, mathematics, systems engineering or a similarly quantitative discipline. Additional education is preferred
• Three (3) or more years of data analysis experience – data wrangling, data munging & statistical analysis
• Two (2) or more years of data visualization and storytelling experience
• Experience programming in SQL and R, and working in a cloud environment (Redshift, EC2, etc.)
• Experience with data visualization (using tools such as Tableau, ArcGIS, D3, etc.)
• Ability to understand business context and translate to develop appropriate data analysis
• Ability to create data mappings, process flows, presentations and reports for documentation
• Demonstrated creative problem solving & critical reasoning abilities
• Adaptability and drive to learn about new data sources, industries, and technologies
• Established ability to communicate effectively and proactively
• Exposure to advanced statistical and machine learning techniques (random forest, support vector machines, neural networks, survival analysis, Bayesian statistics, etc.) and curiosity to learn more
• Perform statistical analysis to provide detailed equipment information for other work teams such as: Marketing, Customer Service and other groups within Finance
• Gain and document a deep understanding of current processes and flows related to the equipment life cycle
• Analyze and identify control gaps within IT architecture and the equipment distribution channels
• Recommend process improvements and determine best ways to improve IT architecture to facilitate equipment processes more efficiently
• Partner with IT to determine which control processes can be automated
• Perform thorough testing of automated processes prior to implementation, and provide feedback on design or code changes
• Incorporate, interpret and report on complex statistical information regarding equipment
• Write complex SQL queries to obtain information from VISION, Point of Sale systems, Rebate Vendors and the Central Returns Warehouse
• Write and test SQL queries and reports to finalize and track equipment activities by business channel
• Analyze and create reporting and audit files. Provide support and feedback defining actions to be taken as a result of the audits
• Maintain and update detailed transaction statistics highlighting changes in trends or volumes and their root cause
• Perform thorough testing of process improvements in UAT as needed. Work with REVO, VISION, and POS to ensure code fixes are implemented as scheduled
• Manipulate complex datasets (sometimes duplicated data) with a range of programming tools
• Support the analytic needs to a business unit by analyzing web traffic using clickstream tools such as Clickstream data in Hadoop and Adobe Analytics etc
• Serve and deliver actionable insights to Marketing, Finance and Product teams
• Lead driving core insights from the data to suggest, create and execute multivariate or a/b/c tests to dive fundamental changes to the site experience
• Senior Business analysts will typically focus their reporting and analysis holistically: clickstream analysis, outcomes analysis, search analysis, and Multivariate testing analysis
• Develop and maintain relationships with the US analytics community
• Deliver world class visualizations and self-serve tools to stakeholders
• Develop business critical reporting to help guide stakeholders decision making and track the growth of the business
• 5+ years’ marketing analytics experience
• Strong commercial experience querying, analyzing and providing insights
• Advanced SQL
• Advanced Excel
• Knowledge of Adobe Analytics (formerly Adobe SiteCatalyst)
• Python or R (statistics, regression, forecasting, time series analysis) – Not essential but very beneficial
• Effective and persuasive verbal and written presentations for project teams and business leaders
• Utilize analytical methods and business acumen to provide analysis, and insights that will assist the Business in moving the needle on our key business metrics. Support your insights with a hypothesis-validation approach with an overall statistically driven framework
• Capable of extracting data from disparate systems to create an end to end perspective
• Adept at identifying and troubleshooting bad data
• Contribute in developing data driven business cases designed to empower decision making at the leadership level
• Provide data as well as insights into SBG's Product and Care delivery experience for our self-employed customers through appropriate analytics methods
• Provide end to end problem-solving and analytical support on business initiatives
• Mentor analysts, specialist and stakeholders on subject matter knowledge and processes to ensure that they are repeatable, sustainable and scalable
• Communicate clearly and effectively to leadership when roadblocks are encountered and assist in their removal
• Understand, as well as work with structured and unstructured data in various forms and channels - community, contact data, web data, marketing data, in-product data, etc
• Participate in decision-making in support of the critical priorities and Care strategy
• Responsible for producing analytic insights that support our business clients’ needs to drive change
• Partner effectively with other analysts and leaders to identify the business problem, negotiate a proposed solution, execute the necessary programming and analytics, present the solution, and track and implement the solution
• Communicate insights and proposals in a clear, concise, and persuasive manner
• Strong advocate of the agile processes and is enthusiastic about working in a team environment to solve problems or complete a large projects
• Strong understanding of analytics methodologies
• 5+ years of experience as a technical data analyst or similar position
• Advanced degree (preferred) in statistics, economics, mathematics, engineering or related field
• Business programming experience in SQL and languages such as SAS, Perl, R and/or big data languages such as Pig, Hive
• Experience with Business Intelligence tools such as Business Objects, Cognos, Actuate, Tableau
• Strong oral, written and presentation skills; ability to communicate across all levels
• Proven track record of analytics project and process management
• Through strong interpersonal skills and teamwork, ability to work with business stakeholders and other analyst teams by building bridges and confronting tough issues that need to be resolved
• Serve as subject matter expert on digital analytics platforms (Google Analytics, and Adobe Analytics)
• Proactively monitor core Google Analytics data sets for oversight including data quality and appropriate configurations to meet business needs
• Provide Google Analytics data/tracking validations, data testing and troubleshooting assistance, including supporting validations on campaign tracking implementation
• Utilize Google Analytics, Webmaster tools (Google Search Console) and XML sitemaps to audit sites to uncover corrections and updates needed
• Assist in maintaining IBM Analytics data set
• Assist in Adobe Analytics implementations, set up and oversight
• Assist in Adobe Test & Target and Recommendations set up and optimization
• Manage implementation/deployment of tracking tags across websites, from initial setup to associated tool configurations
• Implement and update 3rd party tags associated to analytics platforms, testing, usability, SEO, SEM, etc. for collecting and reporting on web activity
• Test, audit and verify tags are implemented properly
• Work collaboratively with front and back end development teams to deliver and release tagging updates into production environments
• Work with vendors to resolve tracking discrepancies
• Run regression testing for code review and data/tagging audits
• JavaScript/jQuery and visualization libraries = 5 years
• HTML/HTML5: 5 years
• W3C DOM methods and properties
• 8+ years maintenance experience tagging and configuring web analytics solutions/platforms, regression testing
• Google Analytics, Google Analytics Universal upgrades,Google Tag Manager
• Aggregation and development of clinical and operational reports to support the business in service line evaluation
• Identify, design and/or recommend resources and analytical methods to support the performance improvement activities to meet organizational goals/needs (i.e. dashboards incorporating clinical and business metrics tailored to strategic or operational goals)
• Develop reports/dashboards and train others on the use of a specific analytics platforms (i.e. Tableau, PowerChart analytics), including coaching about the appropriate procedure available within the platform that will most effectively address a specific problem
• Develop dashboards and scorecards using advanced visualization techniques and data capabilities such as embedding analytics in clinical and business process tools or designing dashboards tailored to strategic goals
• Translate business requirements for dashboard data into accurate business intelligence to meets customer needs while maintaining high standards of methodological integrity
• Function as a consultant to senior leadership about what the data means from a strategic perspective
• Demonstrate expertise in the use of analytical and statistical tools and techniques (e.g., hypothesis testing, statistical process control, distribution, and control charts) to identify when, where, and how to measure processes and systems and make decisions supported by data
• Assess appropriate inclusion/exclusion of data based on defined data dictionary; assists in evaluation of data dictionaries
• Works with Data Analysis & Reporting Manager to develop population based report cards and population based outcome teams regular data reports
• Provides or updates report cards, population based outcome teams regular data reports and other established reports on a regular basis without prompting
• Maintains competency in Midas +, Power Chart, Centricity, PowerInsight, Tableau, SQL, Access, Word, EXCEL, PowerPoint and other applications specific to duties
• Maintains clear documentation and evaluation of work
• Analysis of media campaigns performance using Ad server data and beyond
• Compiling and presenting reports to clients in an easy-to-digest format
• Management and optimisation of our reporting platform, iAnalyse
• Basic knowledge of SQL to query our clients’ data and pull meaningful insight from “big data”
• Management of clients – you will have client facing responsibility and management of various projects
• Strong analytical skills ideally coupled with creative approaches to problem solving
• Ability to juggle a number of tasks at once and consistently deliver to high quality and to timescale
• Ability to build and maintain strong working relationships internally and externally
• Ability to ‘pick up and run’ with projects when necessary
• Complete honesty and confidentiality are essential
• Comfortable working independently, as well as in a team
• Self-starter with entrepreneurial mentality
• Proficiency in creating and presenting to internal and external teams
• Minimum of 2 years of experience with data visualization responsibilities
• Minimum of 2 years of experience working with structured and unstructured data
• Minimum of 2 years of experience working with various databases for various responsibilities
• Bachelor’s degree (BA/BS) from four-year college or university; or equivalent training, education, and experience
• Experience working within the Telecommunications industry
• Experience utilizing Hadoop technology
• Experience coding within HTML5 and Java
• Exhibits integrity though fair and ethical behavior toward others and a demonstrated sense of corporate responsibility and commitment
• Treats colleagues and partners with respect: considers and responds appropriately to the needs, feelings, and capabilities of different people
• Can be relied upon to ensure that projects within areas of specific responsibility are completed in an appropriate and timely manner and acknowledges mistakes, learns from those events and is able to move forward productively
• Ability to balance time to market with a solution and make the right trade-offs along the way
• SQL Server 2008 R2/ SQL Server 2012
• SQL Programming - Partitioning
• Healthcare Claims
• Responsible for working side by side with the SME in initiating, building and writing efficient SQL data mining queries on large and complex data sets
• Responsible for analyzing requirements and implement queries using existing SQL best practices and help recommend best practices for the organization going forward
• Play a leadership role in data and process migration to a new platform
• Play a key role in new client implementation efforts on the new platform
• Collaborating with team members on technology, process and solution support
• Work with business analysts, IT Infrastructure as needed to define and refine requirements
• Bachelor's degree in Computer Science/Computer Engineering/Math
• Use an administrative application and other applications to ensure data integrity
• Coordinate changes to computer databases, test and implement the database applying knowledge of database management systems
• Coordinate, and implement security measures to safeguard computer databases
• Apply statistical theory and methods to collect, organize, interpret, and summarize numerical data to provide data analysis
• Responsible for data analysis on various platforms, documentation and testing, and assist in the management of projects from initial scoping through final delivery and sign-off
• Assist in the evaluation and error detection of the data in the data repository
• Log requests and track the completion of all incoming forms into tracking spreadsheet and/or Access database
• Analyze data for inconsistencies, checks for duplicate data
• Maintain all Corporate Data Services department files/database
• Lead multiple projects and project teams while maintaining current work load
• Mentor junior associates on needs, applications and databases utilized by the data management team
• Bachelor’s Degree in Information Science, MIS, Computer Science or equivalent
• Minimum of 4 years’ of relevant experience
• High level of competency in using applications such as MS Excel, MS Access, Data warehouse database design, SQL Server, SQL Query Design and Oracle
• Minimum 1-3 years’ experience managing Oracle/SQL databases and/or developing efficient SQL queries, stored procedures, indexes, views, functions. Minimum 1-2 years’ experience in data mining techniques and procedures and knowing when their use is appropriate
• Technical expertise regarding data models, and database design development
• Knowledge of Utilization Management and URAC standards is a plus
• Ability to easily and simply communicate with key stakeholders analysis trends and techniques as required
• Must have the ability to work with large sets of data and analyze it to find conclusions. Ability to take a business problem and clearly define ways to solve the problem
• Close attention to detail, conscientiousness of details. Must be vigilant in analysis to come to correct conclusions. Must be thorough and precise
• Ability to define and document processes, process improvements and train members of the team on these processes as they are defined and/or updated
• Excellent organizational and analytical skills required
• Ability to lead various projects and team members, mentor junior associates
• Build data models that integrate disparate information into structured data sets that allow for automated reporting and analysis across the organization
• Analyze complex, ambiguous business problems and communicate results in simple terms
• Serve as thought leader and advisor for analyst team on data management, data analysis, and data visualization
• Communicate informed conclusions and recommendations across the organization’s leadership structure
• Undergraduate degree with strong academic performance in economics, statistics, ISYS or other quantitative field
• 3-5 years of experience analyzing sales, marketing, and/or engineering operations
• Advanced skills in SQL
• Advanced skills in a statistical analysis package (e.g., R, Stata, SAS, SPSS)
• Advanced skills in Tableau
• Strong working knowledge of data warehousing, data architecture, and data visualization
• Experience working with sales and marketing data (e.g., Salesforce.com, Marketo, etc.)
• B2B software experience
• Graduate degree with strong academic performance in economics, statistics, ISYS or other quantitative field
• Expertise in a statistical analysis package (e.g.,R, Stata, SAS, SPSS)
• Identifying trends and patterns within technology incident data – and understanding the behaviors that cause incidents
• Understanding the layers of incident defects and what process, behavior, and design changes technology should incorporate in their thinking
• Lead Problem Management root cause analyses with technical subject matter experts. Diagnosing causes of incidents, determining the resolution, and ensuring that the resolution is implemented
• Prevent problems and eliminate recurring incidents to minimize the impact of incidents
• Responsible for the prevention of recurring business impacting incidents by determining root cause and driving implementation of corrective actions by responsible teams
• Lead the Problem Management process, training and advising users on process, and mentoring first-level associates
• Overseeing process improvement efforts and reporting on the status of enhancements
• Using well tested methods, perform text mining to find meaningful data buried in unstructured text data or extract meaningful numeric indices from the text
• Extract concepts from “large numbers of small documents”
• Lead Business Requirements Gathering process, including the creation of deliverables
• Assist and coach data stewards with developing complex data policies, data metrics, facilitate creation of reports and help them to effectively utilize data to support their roles leveraging best of suite technologies while supporting ACI’s vision
• Design and maintain business processes and systems requirements
• Develop process solutions for longer term strategic direction
• Facilitates data change management impact analysis
• Looking for Quick Wins that can be translated into repeatable processes and implemented as long term strategic solutions
• As needed - evaluate use of Enterprise and SaaS products to meet changing business requirements and continually monitor information needs
• Anticipate business needs, monitor trends in order to recommend functionality enhancements; provide technical advice that enables a customer to solve a problem or improve business processes
• Follows ACI’s business requirement documentation process utilizing the appropriate tools
• Measure the effectiveness of data-related projects. Develop and deliver the benchmarking, identification of best practices, metrics and reporting on health of the Information Governance programs
• Identify new business opportunities available through more effective and creative use of data
• Assist responsible data owners and trustees to ensure appropriate processes and system controls are established and monitored
• Network with external partners to stay abreast of best practices in Information Management, MDM and Information Governance
• Provide gap analysis and stakeholder analysis to show current to future state data impacts
• Partner with the Data Stewards and/or internal partners to build strong cross-functional teams that can work through project challenges
• Ensures consensus and agreement across customers and/or internal partners
• Experience in Information Governance and Master Data Management
• Ability to listen, analyze, discuss and promote solutions with stakeholders while responding to their needs
• Demonstrated leadership skills with experience leading change

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Senior Data Analyst Resume Example & Writing Guide

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Senior data analyst resume sample, professional summary.

Senior Data Analyst with over 8 years of experience in data analysis, data mining, and data visualization. Proficient in SQL, Python, and R. Strong statistical analysis skills and expertise in data modeling and machine learning.

Work Experience

Senior data analyst | abc company.

January 2018 - Present

• Develop data models to analyze customer behavior and predict sales trends resulting in a 15% increase in revenue.
• Develop and maintain ETL pipelines using SQL and Python to automate data collection and processing.
• Create dashboards and visualizations using Tableau to communicate insights to stakeholders.
• Collaborate with cross-functional teams to identify, prioritize, and answer key business questions through the use of data.

Data Analyst | XYZ Consulting

June 2014 - December 2017

• Conducted market research and analyzed customer data to identify growth opportunities resulting in a 10% increase in market share.
• Designed and implemented surveys to collect customer feedback, resulting in actionable insights and a 12% increase in customer satisfaction.
• Created and maintained ETL pipelines using Python and SQL to automate data processing for clients.
• Developed and presented data-driven presentations to clients to communicate insights, recommendations, and solutions.
• Bachelor of Science in Statistics, University of California, Los Angeles
• Master of Science in Data Science, Georgia Institute of Technology
• Data Modeling
• Machine Learning

Focus on Your Achievements

Your resume should showcase what you've accomplished in your career. Instead of listing daily tasks, emphasize your achievements, demonstrating your value with real-world examples.

Senior Data Analyst Resume Writing Guide

Introduction:.

Senior Data Analysts are responsible for analyzing complex datasets, finding insights, and developing actionable business recommendations. They need to be experts in statistics, data mining, and programming languages. Therefore, creating a perfect Senior Data Analyst resume is crucial for any data analyst looking for a career upgrade or a new job. This article will guide you on how to write a Senior Data Analyst resume that will help you stand out from the crowd.

1. Start with an eye-catching Header:

The first part of your resume should introduce yourself to the hiring manager who is going to read it. You can create an eye-catching header that includes your name and contact information such as phone number, email address, and LinkedIn profile.

2. Write an Impactful Summary:

In this section, you need to summarize your professional experience, skills, and achievements in two to three lines. Remember, the hiring manager may not read your entire resume, so your summary should be impactful and compelling. Make sure to tailor it to the job description, and highlight your most relevant accomplishments.

3. State your Professional Experience:

Your professional experience should be listed in reverse-chronological order (most recent first). Each entry should include the name of the company or organization, your job title, dates of employment, and your key responsibilities and achievements. Use bullet points to make it easy to read. Make sure to quantify your results wherever possible, using data to demonstrate the impact of your work.

4. Highlight your Skills:

Your skills should be listed in a separate section, and make sure to include any technical skills or programming languages that are critical for the role. It is also important to mention any certifications, training, or awards that you have earned.

5. Education:

Your education should be listed in reverse-chronological order, just like your professional experience. Include the name of the institution, the degree you earned, and the dates of attendance. If you have any relevant coursework, make sure to mention it.

6. Customize your Resume for Each Job:

Every job is different, so customize your resume for each application. Make sure to include keywords from the job description, and highlight your most relevant experience and accomplishments.

Conclusion:

Writing a Senior Data Analyst resume can be challenging, but if you follow these steps, your resume will stand out from the rest. Remember, focus on your accomplishments, use data to quantify your results, and tailor your resume to each job application. Good luck with your job search!

Common Resume Writing Mistake

Including references.

It's not necessary to include references on your resume unless requested. It is understood that they are available upon request.

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Senior Data Analyst Resume Examples & Writing Guide

The Senior Data Analyst Resume Guide for 2024

Here are our most important resume guidelines we recommend all job seekers follow for a significantly better shot at getting invited for an interview.

Here’s what we’re going to cover in this guide:

• How to properly format your resume for success in 2024
• How to talk about your work experience and personal projects
• How to create a competitive skills section
• How to customize your resume for each job you apply to

Formatting a Senior Data Analyst Resume

Reverse chronological structure: Recent experience first

Reverse chronological resume is the most popular which almost all job seekers should be using. This format means listing out the most recent and relevant things first. It starts with the most recent timeline and you work your way backward, e.g. the latest job position comes first in your work experience section, not the oldest. Structuring your resume this way makes your career timeline more established. 

Senior Data Analyst Resume Length

Stick to 1 page.

Most Senior Data Analysts have found that their best shot at landing an offer is by having a one or two-page resume. This includes a collection of sections that cover relevant past experiences. Your resume should be no longer than three pages. The risk of going beyond two pages is including irrelevant content that could distract from your qualifications.

Avoid Common Senior Data Analyst Resume Format Mistakes

1) Resumes must include as much content as possible.

2) Uniform and labeled section headers

When it comes to creating an ATS-optimized resume, it’s good to know how it will be read by the software. Like most human readers, the ATS will read from left to right and top to bottom. 

3) Minimal white-space

9 Expert Business Resume Examples To Use For Business Related Jobs (Including Writing Tips)

Key Sections for a Senior Data Analyst Resume 

A tailored resume summary .

In a competitive field like Senior Data Analyst, hiring managers sometimes review hundreds of applications for a single position. Writing a resume that stands out is difficult, so solve that problem by including a compelling introduction for your resume. Begin your resume with a resume objective, which is a 2–3 sentence paragraph about your job-relevant skills and career goals.

        Senior Data Analyst at Company A with 4 years of hands-on experience in Java, R, and SQL. Proven ability to conduct extensive data analysis and research to identify trends and drive insights. Seeking new opportunity to leverage strengths in data analytics through collaboration with cross-functional teams to design and implement analytical tools to support enterprise-wide decision making.

          Senior Data Analyst with 7 years of experience in Data Analytics, Tableau and Business intelligence. Demonstrated in-depth understanding of data-driven decision making and ability to scale successful analytics initiatives. Applying for the position of Senior Data Analyst to drive efforts through data analytics and technology.

        Senior Data Analyst with 6 years of experience in SQL, ETL, Database. Proven track record of high quality analysis, recommendations, and high level data visualization. Seeking a Data Analytics position at Company A to gain further expertise in leveraging data to capture growth opportunities.

You can read more about how to create a resume summary with artificial intelligence here.

Your Relevant Professional Experience 

Employers will want to know what you’ve done in your previous job position to get insight into your skills and expertise. Knowing what you’re familiar with will help them make a decision and to see if you’re more of a good fit compared to the other applicants.

However, you should also be including any positive results you’ve accomplished.

Business Certifications

Emphasize your credentials. Include mention of all Important Skills for Business Jobs , Open Certified Data Scientist, Springboard Data Analytics Certification, Certified Analytics Professional(CAP), Associate Certified Analytics Professional, Cloudera Certified Associate Data Analyst, Microsoft Certified : Data Analyst Associate, Microsoft Certified Azure Data Scientist Associate, Certification of Professional Achievement in Data Sciences or other Business methods or processes.

Skills for a Senior Data Analyst Resume

We suggest adding the categorized skills section at the end of your resume. Be sure to include those that are specifically mentioned in the job ad; these are the most important “keywords” that will help rank your resume highly when it is scanned by an automated applicant tracking system during its first round of review.

Hard skills usually include transferable abilities with software, tools and or other professional resources. But don’t forget to include soft skills like teamwork and communication skills, which are necessary to coordinate with an agency, designers, marketing people, business owners and clients. 

Here are more key hard and soft skills that look great on a Senior Data Analyst resume :

Hard skills to consider

• Business programs: Data Warehousing, Machine Learning, Database Query Languages, PSQL, PL/SQL, Programing Languages, R, Python, Data visualization, Statistical Analysis, Data Cleansing, SQL Databases 
• Industry credentials: Open Certified Data Scientist, Springboard Data Analytics Certification, Certified Analytics Professional(CAP), Associate Certified Analytics Professional, Cloudera Certified Associate Data Analyst, Microsoft Certified : Data Analyst Associate, Microsoft Certified Azure Data Scientist Associate, Certification of Professional Achievement in Data Sciences 

Soft skills to consider

• Communication
• Analytical thinking
• Attention to detail
• Product understanding

Business Resume Content

Using metrics to quantify experiences.

Don’t simply fill your resume with lists of your Senior Data Analyst job responsibilities. To impress the hiring manager, put your experience in context with specific examples and hard numbers that prove you’re an accomplished Business Specialist.

Describe how you accomplished something from your previous corporate role. Showcasing the achievements that took place as a result of your contribution will keep the reader engaged. It’s also effective in creating a strong impression and demonstrating your level of ability by highlighting the impact you’ve made.

Without any evidence, it’s hard to trust everything that someone might say. Be factual and take an objective approach. Numbers, figures, and statistics are your best friend. These will make your statements and points a lot more credible. 

Optimizing Resume Content with Business Keywords

How to tailor your resume to a job . Many hiring managers use applicant tracking systems (ATS) to filter applications based on resume keywords they write in their job ads. The more Senior Data Analyst-related keywords you can use, the higher the chances your resume gets past the ATS and onto the hiring manager’s shortlist of applications.

The ATS keyword research process doesn’t have to be difficult. In fact, it’s a straightforward process if you’re doing it with Rezi. Our AI Keyword Targeting feature allows you to upload a job description and instantly see which keywords should be included in your resume's content.

Instantly Generate Senior Data Analyst Resume Content

Job seekers can now use AI to create the perfect application with minimal effort. How long does it take to make a resume writes tailored content instantly and prevents writer’s block completely. It’s that simple yet highly effective in helping you get more job offers and interviews faster. 

All you need to do is enter a few details such as:

• Experience level

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Include a Senior Data Analyst Cover Letter

Many job seekers today overlook the importance of a cover letter . The significant impact it can leave on your recruiters will play its part in the decisive moment for whether you’re going to get hired or not.

To put it simply, cover letters can be your gateway to improving your overall job application and a higher chance of getting the job.

Unless your resume is absolutely perfect with no flaws, why settle for less? A cover letter can greatly increase your odds of getting hired for the company you want to work for, even if it’s a competitive job posting.

Learn more about Rezi AI Cover Letter Builder here

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• • Performed comprehensive data checks and validated ETL summary reports, ensuring the conformance of millions of health records
• • Facilitated the migration of EDW for a large healthcare provider, resulting in a more efficient data processing and a 40% reduction in query runtime
• • Developed and enforced stringent data quality control metrics, improving overall data accuracy by 20%
• • Successfully automated data pipelines using AWS, ensuring 100% availability of critical datasets for the healthcare providers
• • Decreased data discrepancies by 15% by performing regular audits and quality checks
• • Achieved a 100% success rate in mapping target data requirements and data transformations within set timelines
• • Implemented data cleansing procedures, improving data integrity by 25%
• • Automated data management tasks through Python and PySpark, cutting down processing time by 35%
• • Played a key role in the centralization of disparate healthcare data, facilitating a more holistic view of patient care

10 Senior Data Analyst Resume Examples & Guide for 2024

The role of a senior data analyst involves interpreting complex data sets to inform business decisions and drive strategic initiatives. Highlighting experience with data visualization tools, proficiency in statistical analysis, and familiarity with database management systems will strengthen your resume. Emphasizing analytical thinking, advanced Excel capabilities, and programming languages like SQL or Python can enhance your profile. Additionally, mentioning successful projects that led to measurable business improvements and your ability to communicate insights effectively will demonstrate your impact.

All resume examples in this guide

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Resume Guide

Styling your senior data analyst resume: layout and format, strategies for crafting your senior data analyst resume experience section, highlighting essential hard and soft skills for your senior data analyst resume, the importance of your certifications and education on your senior data analyst resume, summary or objective: making your senior data analyst resume shine, how to include other relevant sections for your senior data analyst resume, key takeaways.

Senior data analysts often struggle with effectively communicating the breadth and depth of their analytical skills and project experiences in a concise manner on their resume. Our guide can assist by providing specific tips and templates to help senior data analysts structure their resumes effectively, highlighting their most relevant skills and experience in a way that is both comprehensive and engaging to potential employers.

Dive into our concise guide to learn how to:

• Show your senior data analyst career's brightest moments through your resume's summary, objective, and experience sections.
• Explore top-notch senior data analyst resume examples to understand how to distinguish yourself from other candidates.
• Identify the most sought-after senior data analyst skills and certifications in the industry.
• Design a structured yet unique resume layout.

Recommended reads:

• Data Analytics Manager resume
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• Data Entry Specialist resume
• Junior Data Analyst resume
• Data Entry Operator resume

Pondering the ideal length for your senior data analyst resume? Experts suggest keeping it between one and two pages. Opt for the two-page format if you boast over a decade of pertinent experience. Moreover, the resume format you choose is pivotal in showcasing your experience. Consider the:

• Reverse-chronological resume format to spotlight your career journey;
• Functional skill-based resume format if you're light on experience but want to emphasize skills;
• Hybrid resume format to provide recruiters a comprehensive view of both your experience and skills.

Here are some additional tips for your senior data analyst resume layout :

• Keep your headline straightforward: mention the job you're targeting, a notable certification abbreviation, or your professional specialty;
• Always customize your senior data analyst resume for the specific role, aligning job requirements with your experience in various resume sections;
• After finalizing your resume, save it as a PDF (unless instructed otherwise) to maintain its readability and layout consistency.

Upload your resume

Drop your resume here or choose a file . PDF & DOCX only. Max 2MB file size.

While color can enhance your senior data analyst resume by emphasizing key details like headlines, job titles, and degrees, moderation is key. Stick to a primary and a secondary color to maintain professionalism and avoid a cluttered appearance.

To craft a compelling senior data analyst resume, focus on these sections:

• A scannable header
• A snapshot of your professional persona, showcasing soft skills, achievements, and a summary or objective
• Skills that align with the job advert
• Quantifiable achievements in your experience section
• An education and technical skills section that underscores your proficiency with specific tools or software

What recruiters want to see on your resume:

• Proficiency in data analysis software and programming languages like Python, R, SQL, or SAS.
• Experience with data visualization tools such as Tableau, PowerBI or Google Data Studio.
• Demonstrated ability to interpret complex data and translate it into clear, actionable insights.
• Track record of handling large data sets, cleaning, processing, and conducting rigorous statistical analysis.
• Strong understanding of key business metrics and the ability to communicate effectively to stakeholders about these metrics.
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When detailing your senior data analyst resume experience , it's essential to pair responsibilities with tangible achievements.

Consider including:

• Key responsibilities, emphasizing their significance to your role, team, or organization.
• Experiences that have fostered your technical acumen or professional growth.
• Metrics that underscore your contributions and successes.
• Challenges you've addressed and the solutions you've implemented.
• Strategies you've devised and their measurable impact on growth.

Your experience section is pivotal in making a lasting impression on recruiters. To inspire you, we've curated real-world senior data analyst examples:

• Developed predictive models using machine learning algorithms to optimize marketing campaigns, resulting in a 20% increase in customer conversions.
• Analyzed large datasets to identify trends and patterns, providing actionable insights for business decision-making.
• Collaborated with cross-functional teams to design and implement data-driven solutions, improving operational efficiency by 15%.
• Led the development of a data visualization dashboard, enabling stakeholders to monitor key performance indicators in real-time.
• Conducted A/B testing on website features, resulting in a 25% increase in user engagement and a 10% decrease in bounce rate.
• Performed advanced statistical analysis to identify customer segments and their preferences, leading to personalized marketing strategies.
• Designed and implemented a data warehouse infrastructure, consolidating data from multiple sources and reducing data retrieval time by 30%.
• Developed and maintained automated ETL processes, ensuring timely and accurate data extraction, transformation, and loading.
• Conducted data quality assessments and implemented corrective measures, resulting in a 20% improvement in data accuracy.
• Collaborated with business stakeholders to define project requirements and deliver data-driven solutions, resulting in a 15% increase in sales revenue.
• Performed market segmentation analysis and developed targeted marketing campaigns, resulting in a 30% improvement in customer acquisition.
• Built and maintained data pipelines for collecting and processing large-scale datasets, optimizing data retrieval time by 25%.
• Conducted exploratory data analysis and implemented statistical models to identify factors influencing customer churn, reducing churn rate by 12%.
• Collaborated with the engineering team to deploy machine learning models into production, automating decision-making processes.
• Developed data-driven dashboards using Tableau, providing actionable insights to executive leadership and improving strategic decision-making.
• Managed a team of data analysts, overseeing data collection, analysis, and reporting activities.
• Implemented data quality improvement initiatives, resulting in a 20% reduction in data errors and inconsistencies.
• Collaborated with IT teams to implement data governance policies and ensure compliance with data security regulations.
• Developed and optimized customer segmentation models, enabling personalized marketing campaigns and increasing customer retention by 18%.
• Implemented data visualization tools like Power BI to create interactive reports for executive stakeholders, enhancing data-driven decision-making.
• Conducted ad-hoc analyses to support strategic initiatives, such as pricing optimization and market expansion strategies.
• Collaborated with cross-functional teams to design and implement a data warehouse solution, integrating data from various sources and improving reporting efficiency by 40%.
• Built predictive models using Python and R to forecast customer demand, resulting in a 15% reduction in inventory carrying costs.
• Automated data extraction and transformation processes, reducing manual effort by 80% and improving data accuracy.
• Performed statistical analysis on customer feedback data to identify areas for improvement, leading to a 10% increase in customer satisfaction ratings.
• Developed and maintained data pipelines to support ongoing data analysis and reporting needs.
• Collaborated with business stakeholders to define key performance indicators and establish data-driven targets for performance monitoring.
• Conducted data mining and segmentation analysis to optimize direct marketing campaigns, resulting in a 25% increase in customer response rate.
• Developed and maintained SQL queries to extract data from relational databases for analysis and reporting purposes.
• Provided training and mentorship to junior analysts, promoting a culture of continuous learning and skill development.

Quantifying impact on your resume

• Include quantifiable achievements in your previous roles, such as "Increased data processing efficiency by 20%", to demonstrate your ability to make measurable improvements.
• List specific statistics and data analysis tools you are proficient in, like "Excel", "R", or "Python", to show your technical skills.
• Mention any techniques you've used for handling large datasets, such as "Handled data sets of over 1TB", to show your capability in managing big data.
• Highlight your experience in predictive modeling or machine learning algorithms, like "Implemented machine learning models to predict future sales", to demonstrate your advanced analytical skills.
• Specify if you've led data-driven projects, e.g., "Led a team of 5 analysts on a project that improved marketing ROI by 30%", to showcase your leadership and impact on business results.
• Note if you have experience in data cleaning and preprocessing, as in "Cleaned and preprocessed over 500,000 data points", to highlight your attention to quality and detail.
• Detail any experience with reporting, such as "Created weekly performance reports that increased departmental efficiency by 15%", to show your ability to communicate data effectively.
• Indicate if you've automated processes, for example "Automated data collection process, saving 10 hours per week", to demonstrate your capacity to improve operational efficiency.

Tips for senior data analyst newcomers launching their careers

Lacking extensive experience for that senior data analyst role? No worries.

Sometimes, hiring managers go for the unexpected candidate when they see potential.

Here's how to convince them you're the right fit:

• Opt for the functional skill-based or hybrid formats to highlight your unique professional value.
• Always tailor your senior data analyst resume to emphasize the most critical requirements, usually listed at the top of the job ad.
• Compensate for limited experience with other relevant sections like achievements, projects, and research.
• In your senior data analyst resume objective, pinpoint both your achievements and how you envision your role in the position.
• Resume Without Work Experience
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Remember, the experience section isn't just about traditional roles. It's a space to highlight all professional learning, whether from internships, contract roles, research projects, or other relevant experiences. If it's added value to your skill set for the senior data analyst role, it deserves a mention.

Your skill set is a cornerstone of your senior data analyst resume.

Recruiters keenly evaluate:

• Your hard skills , gauging your proficiency with specific tools and technologies.
• Your soft skills , assessing your interpersonal abilities and adaptability.

A well-rounded candidate showcases a harmonious blend of both hard and soft skills, especially in a dedicated skills section.

When crafting your senior data analyst skills section:

• List up to six skills that resonate with the job requirements and highlight your expertise.
• Feature a soft skill that encapsulates your professional persona, drawing from past feedback or personal reflections.
• Consider organizing your skills into distinct categories, such as "Technical Skills" or "Soft Skills."
• If you possess pivotal industry certifications, spotlight them within this section.

Crafting a comprehensive skills section can be daunting. To assist, we've curated lists of both hard and soft skills to streamline your resume-building process.

Top skills for your senior data analyst resume:

Data Warehousing

Statistical Analysis

Critical Thinking

Communication

Problem-Solving

Attention to Detail

Time Management

Collaboration

Adaptability

Data Visualization

Project Management

Business Acumen

Double-check the spelling of all skills and tools on your resume. Remember, software like the Applicant Tracker System (ATS) scans for these details.

Pay attention to the resume education section . It can offer clues about your skills and experiences that align with the job.

• List only tertiary education details, including the institution and dates.
• Mention your expected graduation date if you're currently studying.
• Exclude degrees unrelated to the job or field.
• Describe your education if it allows you to highlight your achievements further.

Your professional qualifications: certificates and education play a crucial role in your senior data analyst application.

They showcase your dedication to gaining the best expertise and know-how in the field.

Include any diplomas and certificates that are:

• Listed within the job requirements or could make your application stand out
• Niche to your industry and require plenty of effort to obtain
• Helping you prepare for professional growth with forward-facing know-how
• Relevant to the senior data analyst job - make sure to include the name of the certificate, institution you've obtained it at, and dates

Both your certificates and education section need to add further value to your application.

That's why we've dedicated this next list just for you - check out some of the most popular senior data analyst certificates to include on your resume:

Best certifications to list on your resume

• IBM Data Science Professional Certificate - IBM
• Tableau Desktop Certified Professional - Tableau
• SAS Certified Advanced Analytics Professional Using SAS 9 - SAS
• Oracle Certified Professional, MySQL 5.7 Database Administrator - Oracle
• AWS Certified Big Data - Specialty - Amazon AWS

If you have plenty of certifications, prioritize the most relevant and industry-recognized ones. Arrange them based on their relevance to the job at hand.

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Start your resume with a strong summary or objective to grab the recruiter's attention.

• Use a resume objective if you're newer to the field. Share your career dreams and strengths.
• Opt for a resume summary if you have more experience. Highlight up to five of your top achievements.

Tailor your summary or objective for each job. Think about what the recruiter wants to see.

Resume summary and objective examples for a senior data analyst resume

• Seasoned Data Analyst with over 10 years of experience in leveraging data-driven insights to drive business improvement and optimize overall performance. Expert in statistical analysis, data interpretation, and advanced database structures, having led multiple multi-million dollar projects, resulting in a 20% increase in annual revenue.
• High-achieving Software Engineer transitioning into the field of data analysis. With proven abilities in algorithm development and predictive modeling, I have managed to improve software efficiency by 30%. Seeking to apply my robust analytical skills and passion for data in analysing complex data sets in a data-centric organization.
• An accomplished Economist with a wealth of experience in interpreting and analyzing economic data. Aiming to bring my strong command over data analytics and variety of programming languages to effectively tackle complex data problems and contribute to the strategic business decisions in the new field.
• Bringing forward an exceptional academic background in computer science, combined with hands-on experience in machine learning techniques, comprehensive understanding of databases and data visualization tools. Keen to utilize these skills to analyze large datasets and drive significant business improvements.
• Passionate about finding useful information in data, I am eager to bring my strong foundation in statistics and calculus from my degree in Mathematics to a challenging entry-level data analyst position. My goal is to assist in making informed decisions that will lead to increased profitability and growth.
• Graduate with a Masters in Statistics seeking an entry-level data analyst role to utilize my knowledge of statistical methodologies and dedication to interpreting complex datasets. With an unwavering commitment to ensure the accuracy of data, looking to assist a high-growth company in making data-backed decisions.

Apart from the standard sections listed in this guide, you have the opportunity to get creative when building your profile.

Select additional resume sections that you deem align with the role, the department, or the company culture.

Here are the ones we recommend:

• Language skills - use a profficiency framework to indicate your aptitude level;
• Hobbies and interests - you can share more about your favorite books or how you spend your time. It's great for culture alignment;
• Volunteering - helps you highlight the causes you care about and hints at people skills you gained such as teamwork, emotional intelligence, and organizational skills;
• Awards - the space for your most prominent senior data analyst professional accolades and achievements.

Make sure that these sections don't take too much away from your experience, but instead build up your senior data analyst professional profile. You can add them as a second column to your resume, or on a second page.

• Your resume should be a curated narrative, highlighting your alignment with the role's requirements.
• Strategically position your skills, balancing both technical and interpersonal strengths.
• Be selective in detailing experiences, focusing on relevance and impact.
• Utilize the summary or objective to offer a snapshot of your professional essence.
• Across all sections, prioritize authenticity and clarity, ensuring your resume resonates with the senior data analyst role you're eyeing.

Looking to build your own Senior Data Analyst resume?

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Resume Worded   |  Proven Resume Examples

• Resume Examples
• Data & Analytics Resumes

19 Data Analyst Resume Examples - Here's What Works In 2024

The resume is the first step to landing a data analyst role. we interviewed ten hiring managers and recruiters who hire for data analyst roles and found out exactly what they are looking for in 2023. plus, we've compiled six templates you can use when writing your data analyst resume (google docs & pdfs included)..

Data analysts are increasingly becoming one of the most sought after technology roles. Companies are storing terabytes and petabytes of data and need to find ways to effectively use this data to drive business decisions. To do this, they not only need to clean, process and analyze their data, but also need to turn that data into meaningful insights. This is where data analysts come in - i.e. you! In 2023, pretty much every company needs to have a data strategy and, as a result, need to hire data analysts to help with data needs. The first step to getting a data analyst job is a resume. And writing a data analyst resume can be tough if you haven't done it before. In this guide, we've compiled six data analyst resume templates that hiring managers and recruiters have said are among the best data analyst resumes they've seen this year. We've chosen examples of resumes from different stages of the data analyst career path, from entry level to senior level data analysts, so there's a relevant example for you. We've also included links to the PDFs and Google Doc formats, along with specific insight from data-focused recruiters that you can use when writing your own data analyst resume.

Data Analyst Resume Templates

Jump to a template:

• Data Analyst
• Entry Level Data Analyst
• Senior Data Analyst
• Analytics Manager
• Marketing Data Analyst
• Financial Data Analyst
• Experienced Data Analyst
• Junior Data Analyst
• Healthcare Data Analyst
• Business Data Analyst
• Power BI Data Analyst
• Data Analyst Intern

Jump to a resource:

• Keywords for Data Analyst Resumes

Data Analyst Resume Tips

• Action Verbs to Use
• Bullet Points on Data Analyst Resumes
• Frequently Asked Questions
• Related Data & Analytics Resumes

Get advice on each section of your resume:

Template 1 of 19: Data Analyst Resume Example

A data analyst can work in multiple settings by helping companies solve problems through data and statistics. For example, they can work on the marketing team to identify their target audience's shopping habits or trace a disease pattern in a particular area. That’s why they will collect, filter, process, and interpret data. There are many ways to become a data analyst apart from traditional education. You can join an online course, bootcamp, or a certificate program. However, regardless of your educational background, you should emphasize you have advanced training and experience. That’s why it’s a good idea to highlight your data analysis certifications on your resume.

We're just getting the template ready for you, just a second left.

Tips to help you write your Data Analyst resume in 2024

   indicate your knowledge of programming languages..

Depending on your industry and employer, you might get to use a particular programming language to automate data processing. Coding languages like R or Python help data analysts process large sets of data and automate tasks. It is essential to indicate the programming languages you are familiar with on your resume.

   Highlight your data visualization skills.

Even though this is a highly technical occupation, you still need to communicate your results to non-technical stakeholders or team members. That’s why data visualization skills are so important in this role. They help you represent your insights in a more digestible way by using graphics, charts, and even storytelling.

Skills you can include on your Data Analyst resume

Template 2 of 19: data analyst resume example.

This is an effective template you can use if you are applying for all data analyst roles in 2023, and showcases relevant data analyst skill sets in all parts of the resume, including the work experience, skills and projects sections. This resume is ATS-compatible and can be used when applying through online portals. Here's a few more reasons why this data analyst resume template works well:

   Numbers and metrics

Notice how this resume's bullet points makes use of specific numbers while describing accomplishments, e.g. "led to a 25% sales lift". This tells data analyst recruiters that this applicant can make a concrete impact on an organization.

   Good use of space

The two-column in this data analyst resume template prioritizes the work experience sections, while making good use of whitespace. The resume does not look overcrowded and uses reasonable margins.

Template 3 of 19: Entry Level Data Analyst Resume Example

As an entry-level data analyst, you'll be diving into the world of data-driven insights and decision-making. With companies increasingly relying on data for growth and improvement, this role is vital to their success. When crafting your resume, it's essential to demonstrate both your technical skills in data analysis and your understanding of the business context. Keep in mind, employers are looking for candidates with a strong foundation in data manipulation and visualization who can also bring unique insights to the table. In recent years, there's been a shift towards using more advanced tools and programming languages for data analysis, like Python and R. So, ensure your resume highlights your proficiency in these areas, as well as your experience working with databases, data visualization tools, and analytical software. Showcasing your ability to adapt to industry trends will make you stand out among other applicants.

Tips to help you write your Entry Level Data Analyst resume in 2024

   highlight relevant coursework and projects.

As an entry-level candidate, you might not have extensive work experience in data analysis yet. To showcase your skills, focus on relevant coursework, academic projects, or internships that included data analysis tasks. Include specific examples of how you've applied analytical techniques to solve problems or discover insights.

   Demonstrate proficiency in programming languages

Employers often seek data analysts with programming skills in Python, R, or SQL. Make sure to list these languages and any other relevant tools (like Tableau or Power BI) in a "Technical Skills" section of your resume. If possible, include examples of projects that required using these languages to analyze and visualize data effectively.

Skills you can include on your Entry Level Data Analyst resume

Template 4 of 19: entry level data analyst resume example.

If you're a recent graduate or student, use this entry-level data analyst resume template when applying to jobs. It uses extra-curricular and project sections to supplement your work experience.

   University projects

If you are applying for an entry level data analyst job and don't have too much work experience, don't worry! Use data analyst projects like in this resume example to showcase skills like creating predictive models.

   Strong action verbs

Resumes need to use strong action verbs , which immediately tell a recruiter your role in a specific accomplishment. Data analyst resumes should use action verbs that are relevant to data analysis, processing and visualization. Action verbs like "Analyzed", "Assessed" or "Researched" are strong action verbs that effectively showcase data analyst skill sets.

Template 5 of 19: Senior Data Analyst Resume Example

A senior data analyst helps organizations make better business decisions through the use of data and statistical knowledge. They will gather the company’s intelligence and process it to discover actionable insights that help solve a business problem. Hence, senior data analysts will perform data modeling, deep analysis, and forecasting. As a senior data analyst, you might have to supervise less experienced colleagues. Therefore, it is important to mention your ability to monitor team members in your resume. Remember that it’s also important to emphasize your experience in the field.

Tips to help you write your Senior Data Analyst resume in 2024

   demonstrate your impact on previous projects’ success with metrics..

What would you do to showcase your discoveries to your stakeholders? Use metrics and data visualization to represent them. This is the same thing you’ll do with your resume. You should demonstrate your accomplishments with metrics to add tangible value to your resume.

   Indicate your machine learning skills.

Machine learning is an excellent tool that helps you optimize data analytics and data processing. By including this skill in your resume, you are letting your potential employer know that you are up-to-date with the latest industry trends.

Skills you can include on your Senior Data Analyst resume

Template 6 of 19: senior data analyst resume example.

Senior data analyst resumes should have sufficient experience with handling large data sets and experience working cross-functionally. Keep the following in mind too:

   ATS-compatible resume template

Simple templates work well at getting past the automated resume screening stage, also known as the applicant tracking system. Learn how to beat the ATS .

   Strong data analyst skills

Notice how this applicant uses technical data analyst skills in his work experience (e.g. Pentaho Kettle), as well as in a dedicated Technical Skills section at the bottom, where he describes relevant data analyst skills like Python and Excel.

Template 7 of 19: Analytics Manager Resume Example

As an Analytics Manager, you'll be responsible for leading a team of analysts to extract insights from data and drive business decisions. Considering the rapidly evolving nature of this field, it's crucial to stay updated with the latest industry trends and advancements in data analysis tools. When crafting your resume for an Analytics Manager position, emphasize your ability to stay current with industry trends and showcase your strong leadership skills. In your resume, you should highlight your experience in managing analytics projects and delivering actionable insights to stakeholders. It's important to demonstrate your proficiency in a variety of data analysis tools and programming languages, as well as your ability to communicate complex data-driven insights to non-technical team members. Tailor your resume to highlight these key skills and experiences to stand out among other applicants.

Tips to help you write your Analytics Manager resume in 2024

   emphasize data analysis tools and languages.

As an Analytics Manager, you'll need to be proficient in a wide range of data analysis tools and programming languages such as Python, R, SQL, and various data visualization tools. Make sure to highlight your expertise in these areas, including any relevant certifications you may have, to showcase your technical competence.

   Showcase your project management experience

Analytics Managers often lead projects, ensuring their completion on time and within budget. In your resume, describe your experience in orchestrating analytics projects from start to finish, including setting goals, managing resources, and presenting findings to stakeholders. Quantify your achievements when possible to demonstrate the impact of your work.

Skills you can include on your Analytics Manager resume

Template 8 of 19: analytics manager resume example.

Analytics managers are also responsible for managing and monitoring data warehousing. It is the process of collecting data from various sources to discover actionable insights. Some employers might need an analytic manager with warehousing skills. Hence, this is something you might want to mention on your resume. Analytics managers also coordinate data governance, which is the process of maintaining the integrity and security of corporate data. This is another skill you may want to consider including in your resume. Due to the constant data threats, it has become an in-demand skill in the industry.

   Prioritize your technical skills.

Numerous soft skills are essential for an analytics manager's occupation, such as communication, time management, and logical thinking. However, you should prioritize technical competencies, especially in the skills section. This is a highly technical role, so your potential employer might want to know if you are proficient in hard skills like data warehousing, Python, SQL, or data visualization.

   Demonstrate you are up-to-date with the latest industry trends.

Data analytics is a field that requires you to become a lifelong learner, and your potential employer might be looking for that. That’s why you need to demonstrate that you are up-to-date with the latest industry trends. Some of the most recent trends include artificial intelligence and cloud computing.

Template 9 of 19: Analytics Manager Resume Example

Analytics managers are senior-level data analysts that are more focused on managerial responsibilities than on data analyst projects. That said, they need to have a strong understanding of data analysis skill sets, so it's important to include relevant skill sets on your resume.

   Show promotions

For senior data analyst roles, it's important to show recruiters that you have been promoted in the past since this shows leadership. Read this step-by-step guide on how to show a promotion on your resume .

   Relevant experience only

Notice how this analytics manager uses a format on their resume to highlight only impressive accomplishments relevant to the data analyst role they are applying to. Notice how the resume includes a 'Selected Project Experience' which highlights specific analytical projects.

Template 10 of 19: Marketing Data Analyst Resume Example

As a Marketing Data Analyst, you'll be responsible for using data to provide insights and recommendations to marketing teams. This essential role has grown in demand as companies increasingly rely on data-driven decision-making. When writing your resume for this role, it's crucial to showcase your expertise in data analysis, marketing concepts, and communication skills. In today's competitive job market, employers are seeking marketing data analysts who can keep up with the ever-evolving industry trends, such as artificial intelligence, machine learning, and automation. Be sure to highlight your experience and adaptability in these areas on your resume to stand out among other applicants.

Tips to help you write your Marketing Data Analyst resume in 2024

   emphasize marketing and data skills.

When writing your resume, make sure to emphasize your marketing knowledge, such as understanding of customer segmentation, and your data skills, like proficiency in SQL, Python, or R. Demonstrating your ability to combine these skillsets will set you apart as a strong Marketing Data Analyst candidate.

   Showcase relevant projects and results

In the experience section of your resume, highlight relevant projects you've worked on, focusing on the results you've achieved. For example, mention a marketing campaign you've optimized through data analysis, resulting in increased ROI or customer engagement metrics.

Skills you can include on your Marketing Data Analyst resume

Template 11 of 19: marketing data analyst resume example.

Marketing data analysts are essentially data analysts that are focused on marketing and growth initiatives. The skill sets to mention on a marketing data analyst resume are generally exactly the same as other data analyst resumes, but you should also include marketing campaigns or tools in a skills section.

   Target your resume to the job

Resume bullet points describe achievements that are well targeted to the job, such as 'designed campaign strategies'. This is likely aligned to the exact marketing data analyst job description. =

   Good use of action verbs

This data analyst resume uses action verbs like "Identified" and "Spearheaded", which show recruiters that they're a strong data analyst hire.

Template 12 of 19: Financial Data Analyst Resume Example

Financial data analysts are like the fortune tellers of the financial world – they use data to predict future trends and guide business decisions. It's a role that's more complex than ever, especially given the rising influence of big data and AI in the finance sector. When writing your resume, remember that you're not just showing your ability to crunch numbers - you're showcasing your capability to derive meaningful insights from vast amounts of data and convert them into actionable business strategies. The finance industry is evolving fast and companies are relying heavily on data to stay ahead. So, job seekers for this role should reflect that reality in their resumes. This isn't about listing all your past roles and responsibilities; it's about showing how you've used your skills to make a real difference. Companies want analysts who can provide fresh perspectives, help drive efficiencies and enable smart decision-making.

Tips to help you write your Financial Data Analyst resume in 2024

   highlight your quantitative achievements.

Prove your skills with hard data. Instead of simply stating that you're good at data analysis, provide examples where you made a significant impact using your skills. Did your analysis help increase revenue, or reduce costs? Put that in. Quantify your achievements as much as possible.

   Showcase your familiarity with financial systems

You should highlight your experience with financial systems, data platforms, and analytical tools that are widely used in the industry. This might include software like SAS, SQL, Python, or platforms like Oracle, SAP. Mention if you have advanced Excel skills or certification in financial modeling.

Skills you can include on your Financial Data Analyst resume

Template 13 of 19: financial data analyst resume example.

Financial data analysts are just data analysts that are in the financial industry. If you're applying for a data analyst role in 2023, you should include financial data analyst skills like Python and Finance Modeling into your resume.

   Strong resume bullet points

This job seeker uses resume bullet points that are punchy, and most importantly, contain numbers that demonstrate the significance of their accomplishment.

   Leadership and teamwork

This data analyst resume demonstrates good examples of leadership and teamwork with bullet points like 'Managed a cross-functional team'. This tells data analyst recruiters that you have both the hard and soft skills for the job.

Template 14 of 19: Experienced Data Analyst Resume Example

An experienced data analyst collects, stores, and deduces information from large quantities of data. This requires experience with industry-standard data analysis tools, as well as a very analytical and thorough approach to your work. As this position is not an entry-level position, recruiters will be looking to see your previous experience as an analyst as well as an educational history in mathematics, statistics, business, or a similar field. Take a look at this well-structured experienced data analyst resume.

Tips to help you write your Experienced Data Analyst resume in 2024

   include analyst experience outside of data analysis..

There are many transferable skills for analysts in different sectors. So if you have been an analyst outside of data analysis, be sure to include it in your resume. This applicant has included their experience as a financial analyst and business analyst, which are closely related to data analysis.

   Include professional certification and courses in place of a bachelor’s degree.

If you do not have a bachelor’s degree in mathematics, business, statistics, or a similar field, we suggest you pursue professional certification or take online courses. It will indicate to recruiters your level of commitment to your profession and your level of knowledge.

Skills you can include on your Experienced Data Analyst resume

Template 15 of 19: junior data analyst resume example.

A junior data analyst collects and interprets data to help their superiors in their decision-making for the company. As a junior data analyst, you will most likely be working in a team and will be assisting a senior data analyst and/or be answerable to the department head. This position requires collaborative skills as well as strong analytical skills. Recruiters would prefer to see an educational history in mathematics, statistics, or a related field, and a current industry-standard tools list. Take a look at this strong junior data analyst resume.

Tips to help you write your Junior Data Analyst resume in 2024

   show off your collaboration experience..

As a junior data analyst, you will most likely be working as part of a team. So show off any experience where you worked in a team to achieve something impressive. This applicant ‘assisted with developing 7 new mobile apps used by 200k customers’.

   Showcase your tools list.

As a junior data analyst, you will most probably be assigned to do the more grueling data analysis work. Prove to recruiters that you are experienced and capable of doing that by ensuring that your tools list is extensive and current. So if there is a new data analysis tool, ensure you learn how to use it quickly and add it to your tools section.

Skills you can include on your Junior Data Analyst resume

Template 16 of 19: healthcare data analyst resume example.

Healthcare data analysts use data to make beneficial decisions in patient care, medicine, and healthcare center operations. Some of the data you may be looking at includes pharmaceutical data, behavioral data, clinical data, etc. Recruiters will expect you to see a background in the healthcare industry in the experience section of your resume. A bachelor’s degree in a healthcare-related field or a data analysis related field will also be expected. Take a look at this successful resume that shows both.

Tips to help you write your Healthcare Data Analyst resume in 2024

   show your healthcare industry knowledge..

Industry knowledge is particularly important for this position. So be sure to list what sector of healthcare you are particularly knowledgeable about. This applicant has listed health insurance and HIPAA as some of their areas of expertise.

   Include any healthcare industry certification.

Because you will not find a bachelor’s degree called healthcare data analysis, a good way to show that you are particularly knowledgeable and experienced in this particular field/position is to get certification in healthcare data analysis or something very close to that. This applicant has 3 strong related certifications for this position.

Skills you can include on your Healthcare Data Analyst resume

Template 17 of 19: business data analyst resume example.

A business data analyst collates and interrogates data to help with decision-making aimed at optimizing profit and efficiency in a company. This position requires technical skills and also conceptual skills. You will also need to be a good collaborator as you may be working cross-departmentally. A bachelor’s degree in business administration, mathematics, statistics, or a related field would be highly appreciated by recruiters. Extensive experience as an analyst and an up-to-date skills and tools list would also be beneficial.

Tips to help you write your Business Data Analyst resume in 2024

   show your impact on the bottom line..

An easy way to impress recruiters is to quantify your successes. It makes it easier for them to understand your brilliance and helps to set you apart from your competition. This applicant has employed this tactic with much success.

   Highlight your most impressive achievement.

Sometimes your most impressive achievement may get lost amongst your other achievements listed in your ‘work experience’ section. To make sure this doesn’t happen, mention this achievement in the introduction section of your resume. It will be hard for recruiters to miss it.

Skills you can include on your Business Data Analyst resume

Template 18 of 19: power bi data analyst resume example.

As the name suggests, a Power BI data analyst uses Microsoft’s Power BI, to collect and synthesize data to gain information and assist in decision-making in a company. This position requires a Power BI expert, and experience with similar software would be a plus to recruiters as well. As with any other analyst, a recruiter would like to see a bachelor’s degree in mathematics, statistics, or a similar field. But keep in mind that your experience using Power BI is what recruiters will be looking at most. So if you have any Power BI certification, make sure to highlight that.

Tips to help you write your Power BI Data Analyst resume in 2024

   make sure you keep abreast of power bi updates..

Because you are being hired as an expert in Power BI, you need to ensure that you are experienced with the newest version of the software at all times. So make sure you periodically check for updated versions and ensure you mention the newest version of the software in your resume skills section.

   Focus on Power BI keywords/experience only.

Because this is such a specialized position, if you have a wealth of experience in the data analysis field, limit your experience section to Power BI related experience. That is what recruiters will want to concentrate on.

Skills you can include on your Power BI Data Analyst resume

Template 19 of 19: data analyst intern resume example.

A data analyst intern is an entry-level position. You will be working under a superior and will most likely be assigned simple or more mundane tasks as you prove your capabilities. You may not have a lot of experience to list down, so it is important to build out your skills, education, and extra-curricular sections. Take a look at this well-structured resume.

Tips to help you write your Data Analyst Intern resume in 2024

   work on getting certified..

You may not be able to impress recruiters with an extensive work experience section, but where you can impress recruiters and put yourself above your competition is by getting relevant certifications as you prepare to begin your data analyst career. This applicant has 3 impressive certifications.

   Include experience with transferable skills.

You may not have data analysis experience, but you may have other analytical, data-related experience. Even if it is in another field, feel free to include that experience. The skills used are transferable and therefore relevant.

Skills you can include on your Data Analyst Intern resume

As a hiring manager who has recruited data analysts at companies like Google, Amazon, and Microsoft, I've seen countless resumes for this role. The best ones always stand out by showcasing the candidate's technical skills, business acumen, and ability to communicate insights effectively. In this article, we'll cover six essential tips to help you create a compelling data analyst resume that will catch the attention of recruiters and hiring managers.

   Highlight your technical skills and tools

Data analysts use a variety of tools and technologies to collect, process, and analyze data. It's crucial to showcase your proficiency in these areas on your resume. Some key skills to include are:

• Programming languages: Python, R, SQL
• Data visualization tools: Tableau, PowerBI, Google Data Studio
• Statistical analysis software: SAS, SPSS, Stata
• Spreadsheet tools: Microsoft Excel, Google Sheets

When listing these skills, provide specific examples of how you've used them in your previous roles. For instance:

• Used Python and SQL to extract and analyze customer data from a MySQL database, resulting in a 15% increase in customer retention
• Created interactive dashboards using Tableau to visualize sales performance, enabling the sales team to identify top-performing products and regions

   Demonstrate your impact with metrics

Hiring managers want to see the impact you've made in your previous roles. Use metrics to quantify your achievements and show how your work has contributed to business success. Here are some examples:

• Analyzed customer feedback data and identified key drivers of customer satisfaction, leading to a 20% reduction in churn rate
• Developed a predictive model using R to forecast demand for a new product line, resulting in a 25% increase in sales

Avoid using vague or generic statements like:

• Analyzed data to provide insights
• Created reports and dashboards

Instead, be specific about the type of data you analyzed, the insights you uncovered, and the impact your work had on the business.

   Tailor your resume to the job description

Every company has unique data challenges and requirements. To stand out, tailor your resume to the specific job you're applying for. Review the job description carefully and identify the key skills and experiences the employer is looking for. Then, emphasize those skills and experiences in your resume.

For example, if the job description mentions experience with A/B testing, make sure to highlight any relevant projects you've worked on:

• Conducted A/B tests on the company website to optimize user experience, resulting in a 10% increase in conversion rate

Tailoring your resume shows that you've done your research and understand the company's needs. It also helps the hiring manager quickly see how your skills and experiences align with the role.

   Include relevant projects and coursework

If you're a recent graduate or have limited work experience, include relevant projects and coursework on your resume. This can help demonstrate your skills and knowledge to potential employers. For example:

• Capstone project: Analyzed a dataset of 10,000 customer reviews using Python and NLTK to identify sentiment and key themes
• Coursework: Machine Learning (A), Data Structures and Algorithms (A-), Database Systems (B+)

When describing projects, focus on your role, the tools and techniques you used, and the outcomes you achieved. This helps hiring managers understand the depth of your experience and how you can apply it to their organization.

   Showcase your business acumen

Data analysts don't just work with numbers; they also need to understand the business context and communicate insights effectively to stakeholders. Demonstrate your business acumen by highlighting experiences where you've collaborated with cross-functional teams, presented findings to executives, or made data-driven recommendations.

For example:

• Partnered with the marketing team to analyze campaign performance data, identifying opportunities to optimize ad spend and improve ROI by 30%
• Presented quarterly business reviews to senior leadership, communicating key insights and recommendations for strategic decision-making

Showcasing your ability to bridge the gap between data and business strategy will make you a more attractive candidate to potential employers.

   Keep it concise and easy to read

Hiring managers often review dozens of resumes for a single position. To make sure yours stands out, keep it concise and easy to read. Here are some tips:

• Use clear, concise language and avoid jargon or technical terms that may not be familiar to everyone
• Break up long paragraphs into shorter, easier-to-read sections
• Use bullet points to highlight key achievements and skills
• Ensure consistent formatting throughout the document

A well-organized, visually appealing resume will make it easier for hiring managers to quickly identify your qualifications and fit for the role.

Results-oriented data analyst with 5+ years of experience leveraging data to drive business decisions. Proficient in Python, SQL, and Tableau, with a proven track record of collaborating with cross-functional teams to identify opportunities and implement data-driven solutions. Passionate about using data to solve complex problems and deliver meaningful insights.

By following these tips and crafting a compelling resume, you'll be well on your way to landing your next data analyst role.

When writing your data analyst resume, keep in mind the following.

   Structure your bullet points using the Action Verb + Task + Metric framework

Try to always use this framework when writing your bullet points for your data analyst resume. Recruiters are always looking for quantifiable evidence of your impact, and using this framework will ensure you have. Here's what it looks like:

And here's another example:

   Fix your resume's mistakes using Score My Resume

Make sure you upload your resume to Score My Resume to see where you are going wrong and how to improve it.

Writing Your Data Analyst Resume: Section By Section

  header, 1. put your name on its own line.

Your name should be the most prominent part of your header, so it's important to put it on its own line. This will make it easy for hiring managers to quickly identify who you are.

Here's an example of a good name format:

Avoid formatting your name like this:

2. Include your job title

If you're applying for a data analyst position, it's a good idea to include your current or desired job title in your header. This will help hiring managers quickly see that you're a relevant candidate.

Good job title examples:

• Business Intelligence Analyst

Avoid job titles that are too generic or not relevant to data analysis:

• Business Professional

3. Add key contact details

In addition to your name and job title, your header should include your key contact details so hiring managers can easily get in touch with you. At a minimum, include:

• Phone number
• Email address
• LinkedIn profile URL

You can also include your city and state, but there's no need to include your full address. Here's an example of a good contact details format:

[email protected] | 555-123-4567 | linkedin.com/in/johnsmith | Seattle, WA

  Summary

A resume summary, also known as a professional summary or summary statement, is an optional section that goes at the top of your resume, just below your contact information. It provides a brief overview of your professional background, skills, and accomplishments that are most relevant to the job you're applying for.

While a summary is not required, it can be a valuable addition to your resume if you have several years of experience, are changing careers, or want to highlight specific skills or achievements that may not be immediately apparent from your work history. However, if you are a recent graduate or have limited work experience, you may want to skip the summary and focus on other sections of your resume.

It's important to note that you should never use an objective statement instead of a summary. Objective statements are outdated and focus on what you want from an employer, rather than what you can offer them.

To learn how to write an effective resume summary for your Data Analyst resume, or figure out if you need one, please read Data Analyst Resume Summary Examples , or Data Analyst Resume Objective Examples .

1. Tailor your summary to the data analyst role

When writing a summary for a data analyst position, it's crucial to showcase your relevant skills and experience. Hiring managers want to see that you have the technical expertise and analytical mindset needed to succeed in the role.

To do this, highlight your proficiency in key areas such as:

• Data analysis and interpretation
• Statistical modeling and data mining
• Programming languages (e.g., SQL, Python, R)
• Data visualization and reporting
• Problem-solving and critical thinking

For example, instead of a generic summary like this:

Results-driven professional with 5+ years of experience in various industries. Proven track record of success in team environments. Seeking a challenging role that utilizes my skills and experience.

Tailor your summary to the data analyst role:

Data analyst with 5+ years of experience using statistical analysis, data mining, and data visualization to drive business decisions. Proficient in SQL, Python, and Tableau. Proven ability to translate complex data into actionable insights and communicate findings to stakeholders.

2. Quantify your achievements

When possible, use specific numbers and metrics to quantify your accomplishments in your summary. This helps hiring managers understand the impact you've made in your previous roles and how you can contribute to their organization.

For instance, instead of saying:

• Experienced in using data to improve business operations

Quantify your achievement:

• Analyzed customer data to identify opportunities for improvement, resulting in a 15% increase in customer satisfaction scores

Other examples of quantifiable achievements for a data analyst might include:

• Reduced data processing time by 30% by implementing new automation tools
• Developed a predictive model that increased sales by 20%
• Created interactive dashboards that helped executives make data-driven decisions, saving the company $500K annually

By providing concrete examples of your successes, you demonstrate your value and make a stronger case for why you're the best candidate for the job.

  Experience

The work experience section is the most important part of your data analyst resume. It's where you show hiring managers how you've applied your skills to real-world projects and made an impact.

In this section, we'll cover what to include in your work experience section, how to write about your accomplishments, and tips for standing out from other candidates.

1. Focus on relevant data analysis experience

When writing your work experience section, focus on the experience that's most relevant to the data analyst role you're applying for. This could include:

• Analyzing large datasets to identify trends and insights
• Creating data visualizations and dashboards to communicate findings
• Collaborating with cross-functional teams to solve business problems
• Developing and maintaining databases and data pipelines

If you have experience in other areas, like customer service or sales, only include it if you can tie it back to relevant skills for a data analyst, like communication or problem-solving.

2. Highlight your impact with metrics

As a data analyst, metrics are your best friend. Use them in your work experience section to showcase the impact you've had in previous roles. For example:

• Analyzed customer data to identify opportunities for cross-selling, resulting in a 15% increase in revenue
• Created a dashboard to track key performance indicators, reducing time spent on manual reporting by 50%
• Developed a predictive model to forecast inventory demand, reducing stockouts by 20%

Whenever possible, quantify your achievements to give hiring managers a clear picture of your value.

3. Showcase your technical skills

Data analysts use a variety of tools and technologies to collect, analyze, and visualize data. Highlight your technical skills in your work experience section to show hiring managers you have the expertise they're looking for.

For example, instead of just listing 'data analysis' as a skill:

• Conducted data analysis to identify customer trends

Get specific about the tools and techniques you used:

• Analyzed customer data using SQL queries and Python, uncovering insights that led to a 10% increase in customer retention

4. Emphasize your collaboration and communication skills

Data analysts don't work in a vacuum. They often collaborate with cross-functional teams to turn data into actionable insights. Highlight your collaboration and communication skills in your work experience section to show hiring managers you can work effectively with others.

Partnered with the marketing team to analyze campaign data, identifying opportunities to optimize ad spend and increase ROI by 25%

This shows that you can work with other teams to drive business results.

  Education

Your education section is a key part of your data analyst resume. It shows employers that you have the necessary knowledge and training to succeed in the role. Here are some tips to make your education section stand out:

1. Put your education section near the top

If you're a recent graduate or have limited work experience, put your education section near the top of your resume, just below your summary or objective. This will immediately show employers that you have the relevant educational background for a data analyst role.

Here's an example of how to format your education if it's your strongest qualification:

Education Bachelor of Science in Data Science, XYZ University, City, State Graduation: May 2023 GPA: 3.8/4.0 Relevant Coursework: Machine Learning, Data Visualization, Big Data Analytics, Statistical Modeling

2. Include relevant coursework and projects

As a data analyst, you likely took courses and completed projects that are directly relevant to the job. Including these details can make your education section more impactful. List relevant coursework, capstone projects, or your thesis if it shows off data analysis skills.

Here's how you might showcase relevant coursework and projects:

• Relevant Coursework: Data Structures, Algorithms, Database Systems, Data Mining
• Capstone Project: Analyzed customer churn data to identify key factors leading to churn. Built predictive model in Python to forecast churn risk.

3. Add your certifications

Data analysis is a field where certifications carry a lot of weight. If you've earned any relevant certifications, include them in your education section to show your expertise.

Certifications to consider adding:

• Certified Analytics Professional (CAP)
• SAS Certified Advanced Analytics Professional Using SAS 9
• Cloudera Certified Associate (CCA) Data Analyst
• Microsoft Certified: Azure Data Scientist Associate

If you have several certifications, you may want to break them out into their own 'Certifications' section on your resume.

4. Keep it concise if you're experienced

If you're a senior-level data analyst with many years of experience, your education section should be brief. Employers will be more interested in your professional accomplishments. You can simply list your degree, university, and graduation year.

Here's an example of what not to do:

• Master of Science in Applied Mathematics, ABC University, City, State, 2005-2007. Thesis: A Study of Statistical Models for Predicting Housing Prices. Relevant Coursework: Probability Theory, Regression Analysis, Stochastic Processes, Time Series Analysis. GPA: 3.9/4.0

Instead, keep it short and sweet:

M.S. Applied Mathematics, ABC University

Action Verbs For Data Analyst Resumes

Your data analyst resume should contain strong action verbs which effectively describe your accomplishments. Here is a list of action verbs that are popular among strong data analyst resumes. Try not to repeat the same action verb more than twice on your resume. This ensures your accomplishments are unique and stand out.

For a full list of effective resume action verbs, visit Resume Action Verbs .

Action Verbs for Data Analyst Resumes

How to write a data analyst resume.

Here is the process for writing a resume for a Data Analyst role. The steps outlined will guide you to design a resume that shows you have what it takes to clean, process, and analyze business data.

Important information to include in your Data Analyst resume

1.1: include online profiles in your resume header.

Your resume header should include your name, your email address as well as your location. For a specialized role like this, it is advisable to include the job title, Data Analyst, alongside links to your online professional profiles such as GitHub, LinkedIn, and your website.

1.2: List technical Data Analyst skills in the skills section

Adding a skills section will allow you to include keywords that a resume scanner (ATS) is likely to be searching for. Here, you can include relevant hard skills such as 'SQL', 'Python', 'Data Analysis', 'Tableau', and 'Extract, Transform, Load (ETL)'. Organize these skills by proficiency level, and do not list more than 7 items.

Showcase your experience using bullet points

2.1: use strong action verbs and numbers in your bullet points.

Start your bullet points with strong action verbs such as 'Forecasted', 'Analyzed,' and 'Designed'. Action verbs immediately communicate to the recruiter which role you played in a project as a Data Analyst. Your bullet points should always follow the [Action Verb] + [Task] + [Metric] format. Take a look at the following example: Analyzed data from 20000 consumers to develop a multi-tiered pricing model that increased profit margins by 24%. Notice how the bullet point starts with an action verb, 'Analyzed', followed by the task. Also take note of how the bullet point uses a specific number, '24%', to quantify the accomplishment.

2.2: Point out previous promotions to show growth

If applying for a mid or senior Data Analyst role, it is beneficial to demonstrate leadership and managerial skills. You can do this by highlighting promotions that you have received in your past roles. Here are examples of bullet points that demonstrate this: Promoted within one year (a year ahead of schedule) due to strong performance and organizational impact. Promoted to Managing Analyst in 2 years, being the only member in a cohort of 45 Associate Consultants to be fast-tracked

Get past resume scanners (Applicant Tracking Systems)

3.1: use a standard google docs or word template.

Applicant Tracking Systems (ATSs) are automated programs that scan resumes for certain keywords and filter out those that do not meet the role's criteria. To get past the ATS and improve the chances of a Data Analyst recruiter seeing your resume, it is best to make use of Google Docs and Word templates. Be sure to convert your resume to PDF before submitting it.

3.2: Enhance the readability of your resume

Avoid including tables in your resume, as well as the multi-column layout since these can be problematic while parsing by the ATS. Do not submit a scanned copy of your resume as this can make it impossible for the ATS to read.

Finishing touches on your Data Analyst resume

4.1: remove buzzwords and soft skills.

Keywords that describe soft skills such as 'motivated', 'go-getter' and hardworking are best left out of your resume as they serve little purpose. Instead, you should demonstrate these skills through your experience. Below is an example that effectively demonstrates leadership skills without mentioning buzzwords. Deployed the internal tracking system six months ahead of schedule as project manager of an interdepartmental team of 15 people.

4.2: Fix your resume’s mistakes using Score My Resume

It is always a good idea to upload your resume to an online resume checker such as Score My Resume . The free tool will point out areas of your resume that need improvement and catch any errors that you might have missed.

Skills For Data Analyst Resumes

When writing your data analyst resume, you need to make sure you include hard skills in your resume that show recruiters you have the right experience. This not only ensures recruiters put your resume in their 'yes' pile, but this is also ensures your resume will make it past the initial resume screening stage (i.e. the applicant tracking system ). To help you get started, here are keywords and hard skills from data analyst jobs we've analyzed. To find keywords relevant to the job you're applying to, use Targeted Resume . You should always ensure you tailor your resume to the data analyst job posting you apply to. This will maximize your chances getting an interview.

• SAS Programming
• Data Analysis
• Clinical Data Management
• Healthcare Information Technology (HIT)
• Data Visualization
• Electronic Medical Record (EMR)
• Clinical Research
• R (Programming Language)
• Microsoft SQL Server
• U.S. Health Insurance Portability and Accountability Act (HIPAA)
• Data Analytics
• Healthcare Analytics
• Clinical Trials
• Data Management
• Electronic Data Capture (EDC)
• Healthcare Management

How To Write Your Skills Section On a Data Analyst Resumes

You can include the above skills in a dedicated Skills section on your resume, or weave them in your experience. Here's how you might create your dedicated skills section:

Skills Word Cloud For Data Analyst Resumes

This word cloud highlights the important keywords that appear on Data Analyst job descriptions and resumes. The bigger the word, the more frequently it appears on job postings, and the more 'important' it is.

How to use these skills?

Resume bullet points from data analyst resumes.

You should use bullet points to describe your achievements in your Data Analyst resume. Here are sample bullet points to help you get started:

Liaised with marketing to drive email and social media advertising efforts, using predictive modeling and clustering, resulting in a 35% increase in revenue

Built Tableau dashboard to visualize core business KPIs (e.g. Monthly Recurring Revenue), saving 10 hours per week of manual reporting work

Analyzed global opportunities for the company's different membership tiers; designed and introduced a new membership tier which is projected to generate 300k new users in its first year

Created Monte Carlo simulation using Pandas (Python) to generate 30,000 sample portfolios with 8+ constraints

Designed the data pipeline architecture for a new product that quickly scaled from 0 to 100,000 daily active users.

For more sample bullet points and details on how to write effective bullet points, see our articles on resume bullet points , how to quantify your resume and resume accomplishments .

Frequently Asked Questions on Data Analyst Resumes

What should a data analyst put on a resume.

• Header section: Here, include a link to an online profile such as LinkedIn or your portfolio. Your portfolio should showcase your work using visuals, dashboards, and graphs so it can be understood by non-technical hiring managers. It is also a good idea to include your job title—Data Analyst, alongside your name and country/city.

Analyzed data from 20000 consumers to develop a multi-tiered pricing model that increased profit margins by 24%.

• Education: Here, list your qualifications in analytics, statistics, computer science or equivalent areas. Keep this section brief, listing just the certification name, school, and graduation date.
• Skills section.

What skills should you put on a data analyst resume?

How do i improve my data analyst resume, other data & analytics resumes, engineering manager.

Integration Architect

Data Analyst Resume Guide

• Data Engineer Resume Guide
• Business Analyst Resume Guide
• Data Scientist Resume Guide
• Data Mining Resume Guide
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• Actuarial Science Resume Guide
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• Big Data Resume Guide
• Intelligence Analyst Resume Guide
• Director of Analytics Resume Guide
• Reporting Analyst Resume Guide
• Data Governance Resume Guide
• Data Specialist Resume Guide
• Machine Learning Resume Guide
• GIS Resume Guide
• Data Analyst Resume Example
• Entry Level Data Analyst Resume Example
• Senior Data Analyst Resume Example
• Analytics Manager Resume Example
• Marketing Data Analyst Resume Example
• Financial Data Analyst Resume Example
• Experienced Data Analyst Resume Example
• Junior Data Analyst Resume Example
• Healthcare Data Analyst Resume Example
• Business Data Analyst Resume Example
• Power BI Data Analyst Resume Example
• Data Analyst Intern Resume Example
• Tips for Data Analyst Resumes
• Skills and Keywords to Add
• Sample Bullet Points from Top Resumes
• All Resume Examples
• Data Analyst CV Examples
• Data Analyst Cover Letter
• Data Analyst Interview Guide
• Explore Alternative and Similar Careers

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3+ Senior Data Analyst Resume Examples and Templates

This page provides you with Senior Data Analyst resume samples to use to create your own resume with our easy-to-use resume builder . Below you'll find our how-to section that will guide you through each section of a Senior Data Analyst resume.

How to Write a Senior Data Analyst Resume?

To write a professional Senior Data Analyst resume, follow these steps:

• Select the right Senior Data Analyst resume template.
• Write a professional summary at the top explaining your Senior Data Analyst’s experience and achievements.
• Follow the STAR method while writing your Senior Data Analyst resume’s work experience. Show what you were responsible for and what you achieved as a Senior Data Analyst.
• List your top Senior Data Analyst skills in a separate skills section.

How to Write Your Senior Data Analyst Resume Header?

Write the perfect Senior Data Analyst resume header by:

• Adding your full name at the top of the header.
• Add a photo to your resume if you are applying for jobs outside of the US. For applying to jobs within the US, avoid adding photo to your resume header.
• Add your current Senior Data Analyst to the header to show relevance.
• Add your current city, your phone number and a professional email address.
• Finally, add a link to your portfolio to the Senior Data Analyst resume header. If there’s no portfolio link to add, consider adding a link to your LinkedIn profile instead.
• Bad Senior Data Analyst Resume Example - Header Section

Daniel 7600 W. Bay Meadows Avenue Rochester, NY 14606 Marital Status: Married, email: [email protected]

• Good Senior Data Analyst Resume Example - Header Section

Daniel Gilbert, Rochester, NY, Phone number: +1-555-555-5555, Link: linkedin/in/johndoe

Make sure to add a professional looking email address while writing your resume header. Let’s assume your name is John Doe - here is a formula you can use to create email addresses:

• [email protected] - [email protected]
• [email protected] - [email protected]
• [email protected] - [email protected]
• [email protected] - [email protected]
• [email protected] - [email protected]
• [email protected] - [email protected]

For a Senior Data Analyst email, we recommend you either go with a custom domain name ( [email protected] ) or select a very reputed email provider (Gmail or Outlook).

How to Write a Professional Senior Data Analyst Resume Summary?

Use this template to write the best Senior Data Analyst resume summary: Senior Data Analyst with [number of years] experience of [top 2-3 skills]. Achieved [top achievement]. Expert at [X], [Y] and [Z].

How to Write a Senior Data Analyst Resume Experience Section?

Here’s how you can write a job winning Senior Data Analyst resume experience section:

• Write your Senior Data Analyst work experience in a reverse chronological order.
• Use bullets instead of paragraphs to explain your Senior Data Analyst work experience.
• While describing your work experience focus on highlighting what you did and the impact you made (you can use numbers to describe your success as a Senior Data Analyst).
• Use action verbs in your bullet points.

Senior Data Analyst Resume Example

Senior Data Analyst

• Detection of data quality issues and informing appropriate stakeholders for amendment.
• Managed PowerBI developer to deliver two comprehensive sets of Power BI Dashboards to support business performance reporting needs and regulatory Member Outcomes Assessment needs.
• Customer Analysis: Analysed, identified and confirmed deceased customer data set for the Significant Event Notifications on AMPL separation.
• Provided insights through data analysis on business performance.
• Sourcing superannuation data from multiple sources, data modelling, profiling, analysing, building metrics and managing PowerBI Developer in building visualisation to support ACME quarterly reporting.
• Leading and developing data analysts.
• Performing analysis to provide insights to business for regulatory requirements on business performance and member outcomes.
• Identified gaps in data collection, management and analysis within Participation, and plan methods to introduce new processes, training, and tools to make incremental improvements.
• Supported and provided guidance for colleagues on best practice for data collection, management, analysis, and visualization to make the most of their audience and operational data.
• Managed, maintained, and continued to develop Power BI dashboard data model and reports which demonstrate the UK-wide reach of our engagements.
• Worked with key stakeholders to understand organizational goals and identify data collection, analysis, and visualization projects to support these goals.
• Used data analytics to drive evidence-based decision-making, improve customer experience and optimize operational efficiency
• Experience on AWS for deployments using DevOps tools.
• Work based on Agile scrum framework.
• Generate operation reports and audit reports from different data sources available.
• Analyze daily and weekly operation reports and perform audits for any financial mismatches.
• Work on reports to create weekly budgets and expense reports.
• Also, experience working with visualization tools like tableau.
• Excellent communication, articulation and presentation skills to handle global deliverymodels. Experience working with US clientele.
• Worked on testcases using Cypress/Jest tools and generate test reports.
• Manage DevSecOps practices for these environments i.e. GIT repos, Merge approvals, Jenkins pipeline management, Sonar integration.
• Creating Monitoring dashboards for app environments.
• Work on monitoring the environments using AWS Cloudwatch/Kinesis Delivery Streams/NewRelic logs/metrics.
• Discovery, refinement, and support of real estate valuation systems.
• Analyzed large datasets and identified a significant number of records in multiple counties nationwide with various address issues.
• Took major part in creation and fine-tuning of a value estimation engine ACME; performed data mining, analysis, and data integrity tasks for property appraisal emulation, repeat sales, and tax assessed valuation models.

Senior Data Analyst-Business Intelligence Resume Example

Senior Data Analyst-Business Intelligence

• Corporate policy portfolio improvement and revamp.
• Construct revenue models through employee behavior forecasting to predict monthly profit.
• Conduct organizational sales analysis and report weekly sales figures to directors board and upper management.
• Deliver client-facing advanced analytics projects.
• Develop, implement, and adhere to data modeling standards and best practices.
• Implement ad-hoc projects as required, developed R scripts for generating financial and water usage summary reports, and Optimized existing code to improve performance.
• Analyze trends in complex data sets to identify current and future issues.
• Deliver relevant data and insight into products and services to meet the business needs of our Partners.
• Gathering business requirements that are related to KPIs and Dashboards
• Designing and Building dashboards using Tableau Desktop
• Uploading the dashboards to Tableau Server
• Leading technical activities for data governance and Data platform Project
• Working on data governance regulations, data classification, data quality, data storage, data structure and modeling data
• Lead Data Analyst responsible for Business Analysis and Data Management activities on a multi-year program to introduce a Compliance Data Warehouse
• Acted as a trusted technology partner and recognised SME stakeholders and IT teams, advising on key topics ranging from Data Sourcing through to defining the yearly budgeting process
• Perform UAT Session for dashboards with internal department
• Build dashboard to identify data quality issues
• Gather Business requirements then prepare BRD – Business Requirements Documents
• Design, develop and maintain a dashboard using Power BI Desktop and Power Services
• Work with management to prioritize business and information needs
• Maintain, upgrade and support Business Intelligence Platform
• Development and implementation of database queries and cleansing the data before analyses
• Collecting, cleaning, and processing data using SQL from databases
• Troubleshooting the reporting database environment
• Create visualizations and reports for requested projects from the business team
• Build, develop data warehouses and Highlighting findings, and recommendations
• Build classification models based on Random Forest, XG Boost Classifier to predict the default of claim.
• Identify opportunities like tail spend, payment term optimization, cost benchmarking and external commodity market fluctuations and work with global category managers to explore, plan and implement relevant solutions.
• Coordinated with Inspector General office to detect and audit the fraudulent activities in the fund claims.
• designed developed and deployed the fraud detection model it identify and flag the suspicious claims done by the principle NGO's.
• Analyzing the market trend to get the pulse of core products for procurement and mapping the suppliers to those products and preparing category catalog.
• Implemented Big Data Analytics and Data Science techniques to identify trends, patterns, and discrepancies on large scale of data by using Sparkql, Hiveql.
• Performed data cleaning, dealing with extreme outliers and explored data to draw relationships and correlations between variables.
• Principal Component Analysis (PCA) used as dimensionality reduction technique in the pre-processing step for pattern-classification and machine learning model.
• Mastered the ability to design and deploy rich Graphic visualizations with Drill Down and Drop-down menu option and Parameters using Tableau.
• Worked closely with Business users. Interacted with ETL developers, Project Managers, and members of the QA teams.
• Provided Production support to Tableau users and Wrote Custom SQL to support.
• Converted existing BO reports to tableau dashboards.
• Created different KPI using calculated key figures and parameters.
• Developed Tableau data visualization using Cross tabs, Heat maps, Box and Whisker charts, Scatter Plots, Geographic Map, Pie Charts and Bar Charts and Density Chart.
• Conduct external market research including key industry, market and category/commodity information to assist in strategic purchasing decisions.
• Timely translation and communication of industry data into reports and charts and management of Internal and External Databases.
• Designed, developed, tested, and maintained Tableau functional reports based on user requirements.

Senior Data analyst Resume Example

Senior Data analyst

• Collaborated with IT heads to identify opportunities for operational improvement and strategic decisions in respective functions based on data.
• Defined and tracked key performance indicators for existing and few functions/projects across the company.
• Conducted detail analysis, generated insights and visualizations and published reports based on company-wide data.
• Improved Data accuracy, viability and value by improving and streamlining processes regarding data flow and data quality.
• Monitored expenses, expenses, sales and revenue, conducted weekly reports and presented findings and results to managers and executives.
• Tracked and fixed any data discrepancies.
• Ensure consistency, completeness and accuracy of data in all databases from different nodes on the network.
• Analyze data from all databases to ensure accurate billing is made for all business transactions.
• Interface between the Site Reliability Engineers and the business data analysis team to monitor data availability, latency, and data pipeline and system performance.
• Help business make the best decisions by providing internal and external reports on leakage detection, revenue assurance and quality observations.

Top Senior Data Analyst Resume Skills for 2023

• Data analysis
• Data mining
• Data modeling
• Data visualization
• Statistical analysis
• Predictive modeling
• Machine learning
• Regression analysis
• Time series analysis
• Cluster analysis
• Classification algorithms
• Natural Language Processing (NLP)
• Text mining
• Sentiment analysis
• Feature engineering
• Dimensionality reduction
• A/B testing
• Hypothesis testing
• Statistical inference
• Data preprocessing
• Data cleaning
• Data wrangling
• Data transformation
• Data integration
• Data validation
• Database querying (SQL)
• Data warehousing
• Data governance
• Data quality assurance
• Data architecture
• Data visualization tools (e.g., Tableau, Power BI)
• Statistical software (e.g., R, Python, SAS)
• Data manipulation libraries (e.g., pandas, dplyr)
• Machine learning libraries (e.g., scikit-learn, TensorFlow)
• Big data technologies (e.g., Hadoop, Spark)
• Cloud computing platforms (e.g., AWS, Azure, Google Cloud)
• Business intelligence tools (e.g., Looker, QlikView)
• Excel (advanced functions, pivot tables, macros)
• Data storytelling
• Dashboard design
• ETL (Extract, Transform, Load) processes
• Data governance frameworks
• Data privacy regulations (e.g., GDPR, CCPA)
• Data security best practices
• Project management skills
• Communication skills
• Problem-solving skills
• Critical thinking

How Long Should my Senior Data Analyst Resume be?

Your Senior Data Analyst resume length should be less than one or two pages maximum. Unless you have more than 25 years of experience, any resume that’s more than two pages would appear to be too long and risk getting rejected.

On an average, for Senior Data Analyst, we see most resumes have a length of 2. And, that’s why we advise you to keep the resume length appropriate to not get rejected.

Frequently Asked Questions (FAQs) for Senior Data Analyst Resume

What does a Senior Data Analyst do?

• A Senior Data Analyst is responsible for analyzing complex datasets, interpreting trends, and providing insights to support strategic decision-making within an organization. They lead data analysis projects, develop analytical solutions, and communicate findings to stakeholders.

What qualifications are important for a Senior Data Analyst position?

• Qualifications typically include a bachelor's or master's degree in data science, statistics, mathematics, computer science, or a related field. Extensive experience in data analysis, proficiency in analytical tools such as SQL, Python, R, or SAS, and strong communication and leadership skills are essential.

What kind of experience should a Senior Data Analyst highlight on their resume?

• Experience in data analysis, statistical modeling, machine learning, and data visualization techniques is crucial for a Senior Data Analyst. Highlighting proficiency in interpreting complex data sets, designing analytical frameworks, and presenting insights to senior management is important.

How important is it for a Senior Data Analyst to demonstrate leadership skills on their resume?

• Leadership skills are vital for a Senior Data Analyst as they often lead cross-functional teams and drive data-driven initiatives within an organization. Highlighting experience in project management, mentoring junior analysts, and influencing decision-making processes can demonstrate effective leadership abilities.

Should a Senior Data Analyst include their experience with data storytelling on their resume?

• Yes, mentioning experience with data storytelling techniques, including creating compelling narratives, visualizations, and presentations to communicate insights effectively to non-technical audiences, can demonstrate the Analyst's ability to drive actionable insights and influence decision-making.

What soft skills are important for a Senior Data Analyst to highlight on their resume?

• Soft skills such as communication, critical thinking, problem-solving, adaptability, collaboration, and strategic thinking are crucial for a Senior Data Analyst. These skills contribute to effectively translating data into business insights and driving organizational change.

Is it necessary for a Senior Data Analyst to mention their experience with data governance and compliance on their resume?

• Yes, mentioning experience with data governance frameworks, compliance regulations such as GDPR or HIPAA, and data security best practices can demonstrate the Analyst's commitment to ensuring data integrity, privacy, and security in their analytical work.

How should a Senior Data Analyst tailor their resume for different industries or functional areas?

• A Senior Data Analyst should highlight experience and skills relevant to the specific industries or functional areas they have worked in, whether it's finance, healthcare, e-commerce, or marketing. Emphasizing familiarity with industry-specific metrics, business challenges, and analytical solutions can be beneficial.

Should a Senior Data Analyst include their educational background on their resume?

• Yes, including educational background such as degrees, certifications, or relevant coursework in data analysis, statistics, or data science is important. This provides credibility and demonstrates the foundational knowledge necessary for the role.

How can a Senior Data Analyst make their resume visually appealing and easy to read?

• Utilizing clear headings, bullet points to highlight key skills and experiences, and a professional layout are important aspects of resume formatting. Additionally, including specific examples of data analysis projects completed, business impact achieved, or any relevant achievements or recognitions can enhance the overall presentation of the resume.

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Senior Data Analyst Resume Examples

Writing a strong resume for a Senior Data Analyst role can be a challenge. Your resume needs to capture the attention of the recruiter in order to get noticed and land an interview. It should demonstrate your knowledge of data analysis, the industry and the specific skills that the company is looking for. To help you craft an effective and persuasive resume, this guide will cover the basics of resume writing, including the common elements of a resume, tips on how to highlight your skills, and relevant examples of successful resumes. With these strategies in hand, you will be able to confidently create a resume that imparts your qualifications, experience and talents.

If you didn’t find what you were looking for, be sure to check out our complete library of resume examples .

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Senior Data Analyst

123 Main Street | Anytown, USA 99999 | Phone: (123) 456-7890 | Email: [email protected]

A highly motivated and results- driven Senior Data Analyst with over 7 years of experience in data collecting, analyzing, and reporting. Possess strong analytical and problem- solving skills to identify trends and patterns in data. Experienced in using Excel and SQL to develop databases and reports. Highly skilled in providing accurate and timely conclusions in order to support business decisions. Proven track record of developing insights in data to identify areas of opportunity and growth.

Core Skills :

• Advanced Excel & SQL experience
• Data mining & data analysis
• Knowledge of ETL processes & procedures
• Excellent problem- solving & decision- making
• Proficient in reporting & dashboard creation
• Excellent communication & presentation
• Knowledge of statistical models
• Strong organizational & time- management

Professional Experience :

• Senior Data Analyst, ABC Company, 2020- present
• Developed and maintained data dashboards & reports to provide data- driven insights to higher- level management
• Conducted data analysis to identify trends, patterns, and areas of opportunity
• Collected, organized, and analyzed data from various sources to produce key findings
• Developed & maintained ETL pipelines and wrote SQL scripts to ensure data accuracy & consistency
• Optimized data collection & analysis processes for improved efficiency
• Data Analyst, XYZ Company, 2017- 2020
• Managed and monitored data quality to ensure accuracy in data collection
• Developed & maintained data warehouses and ETL pipelines
• Utilized Excel & SQL to create reports & dashboards to capture & address key business opportunities
• Used statistical models to assess trends & performance
• Provided timely and frequent insights & conclusions to support decision- making processes

Education :

• Bachelor of Science in Computer Science, ABC University, 2013- 2017
• Basic & Advanced Data Analytics Certificate, XYZ Institute, 2018

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Senior Data Analyst Resume with No Experience

A highly motivated and results- oriented professional with a strong interest in data science and analytics. Proven ability to work in a fast- pace environment with strong analytical and problem- solving skills. A quick learner and highly organized with excellent communication and interpersonal skills.

• Experience with MS Office and analytical software applications
• Strong understanding of data analysis processes and principles
• Knowledge of SQL and data visualization tools
• Proficient in development of data- driven insights
• Ability to develop and implement data models
• Excellent analytical and problem- solving skills

Responsibilities :

• Analyze complex data and generate actionable insights
• Develop, maintain, and analyze data models to identify trends and anomalies
• Review and evaluate existing data analysis processes and procedures
• Design and develop data- driven reports and dashboards
• Identify opportunities for process improvement and increased efficiency
• Monitor key performance indicators and metrics to ensure data accuracy and consistency

Experience 0 Years

Level Junior

Education Bachelor’s

Senior Data Analyst Resume with 2 Years of Experience

Self- motivated Senior Data Analyst with 2 years of experience in helping organizations identify trends, create detailed reports and uncover insights through the examination of large data sets. Adept in leading a team and training junior analysts, as well as developing customized data- driven solutions that reduce costs and increase efficiency. Proven track record of success in analyzing data to develop strategies and identify opportunities.

• Data Visualization and Modeling
• Data Science and Machine Learning
• Data Mining and Analysis
• Data Warehousing and ETL
• Programming (Python, SQL, R, Tableau)
• Project Management
• Business Intelligence
• Statistical Analysis
• Problem- Solving
• Develop and maintain data mining models and reporting systems for predictive analytics
• Analyze large data sets to identify trends, improve operations and develop strategies
• Lead a team of junior analysts in data collection and analysis
• Design and implement data warehouse systems for storing large and complex data sets
• Utilize data science and machine learning techniques to develop predictive models
• Generate reports, graphs and dashboards in Tableau to summarize and visualize data
• Develop and maintain automated processes to streamline data analysis
• Create and maintain documentation on data analysis processes
• Train and mentor junior analysts on data analysis techniques and best practices

Experience 2+ Years

Senior Data Analyst Resume with 5 Years of Experience

I am an experienced Senior Data Analyst with 5+ years of experience working with a wide range of data sources to develop strategies and solutions to meet specific business goals. I have advanced proficiency in a variety of data analysis techniques, as well as the ability to identify patterns, trends, and correlations. I am an excellent communicator, able to present complex data in a user- friendly format. I am also highly motivated, organized, and reliable, able to produce results in a timely manner.

• Data analysis
• Data mining
• Data visualization
• Problem solving
• Project management
• Collect, analyze, and interpret large amounts of data from multiple sources.
• Monitor and analyze data trends and correlations to identify areas for improvement.
• Design and develop reporting and analytics tools to provide better insight into business performance.
• Develop strategies and solutions to meet specific business goals.
• Produce accurate and timely reports for both internal and external stakeholders.
• Create data visualizations to emphasize trends and correlations.
• Develop and maintain databases and other data systems.
• Utilize SQL and Excel to extract and analyze data.
• Identify and assess potential risks associated with data analysis projects.
• Collaborate with other departments to develop data solutions.
• Stay up to date on the latest trends in data analysis.

Experience 5+ Years

Level Senior

Senior Data Analyst Resume with 7 Years of Experience

Highly experienced Senior Data Analyst with 7+ years of experience in analyzing complex data, creating meaningful insights, and developing strategies for process optimization. Expertise in data mining, data visualizations and predictive analytics in developing highly effective reporting. Experienced in creating dashboards, databases and data models with an in- depth understanding of data warehousing and analytics tools. Proven ability to quickly understand customer needs and develop customized solutions.

• Data Mining
• Data Visualization
• Predictive Analytics
• Data Warehousing
• Analytics Tools
• Data Modeling
• Dashboard Development
• Database Development
• Develop and implement data analysis, data modeling and mining strategies
• Create visually appealing data visualizations to present data effectively
• Analyze customer data to identify trends and areas of improvement
• Develop and utilize predictive analytics to identify high- value opportunities
• Provide insights and recommendations to improve operational efficiencies
• Create databases, dashboards and reports to track performance metrics
• Collaborate with stakeholders to identify data requirements
• Identify and address data quality issues to ensure accuracy and completeness
• Provide ad- hoc analysis and reporting as requested by stakeholders.

Experience 7+ Years

Senior Data Analyst Resume with 10 Years of Experience

Senior Data Analyst with 10 years of experience in the field of data analysis and manipulation. Strong background in analyzing, interpreting and presenting complex data sets. Highly skilled in leading the design, development, and implementation of large- scale data analysis initiatives. Experienced in the development of data- driven solutions, models, and reports. Adept at creating datasets, generating data- driven insights and presenting them in a professional manner to stakeholders.

• Extensive knowledge in data analysis, manipulation and management
• Advanced expertise in data modeling, data mining and ETL processes
• Familiarity with various reporting and visualization tools
• Proficient in SQL, Python, R and other statistical programming languages
• Strong communication, collaboration, and interpersonal skills
• Analyze large datasets to identify patterns, insights, correlations, and trends.
• Develop and implement data management and analysis processes.
• Analyze customer data to identify customer needs, preferences, and trends.
• Perform data mining and analysis to ensure that data is relevant and accurate.
• Develop and maintain event- driven data pipelines.
• Develop and maintain data models to track performance metrics.
• Design, develop, and implement data- driven solutions and initiatives.
• Develop and create datasets and reports as needed.
• Analyze customer data to recommend strategies and tactics to improve efficiency and effectiveness.
• Design and develop data- driven reports, presentations, and visuals.
• Provide data analysis and reporting to stakeholders.

Experience 10+ Years

Level Senior Manager

Education Master’s

Senior Data Analyst Resume with 15 Years of Experience

I am a senior data analyst with over 15 years of professional experience in the field of data science and analytics. I have developed a strong set of skills in the development and implementation of analytics models, and I have a deep understanding of data- driven decision- making. I am adept at data analysis, data mining and data visualization techniques, and I have a proven track record of success in delivering high- quality and high- impact data analysis projects on time and on budget.

• Highly- skilled in data analysis, data management and data modeling
• Expertise in data visualization and data mining techniques
• Experience in developing and implementing analytics models
• Proficient in data- driven decision- making
• Excellent communication and problem- solving skills
• Proficient in various analytical tools and software
• Analyze large data sets to identify patterns, trends, correlations and anomalies
• Develop and maintain predictive models to forecast future trends and outcomes
• Perform data mining and data modeling to identify new insights from data sources
• Generate reports and visualizations to communicate analytical results
• Audit and validate data accuracy and integrity
• Develop and implement data management processes and procedures
• Provide technical guidance and support in data analysis and decision- making

Experience 15+ Years

Level Director

In addition to this, be sure to check out our resume templates , resume formats ,  cover letter examples ,  job description , and  career advice  pages for more helpful tips and advice.

What should be included in a Senior Data Analyst resume?

As the demand for data-driven decision-making increases, so too does the need for experienced Senior Data Analysts. A Senior Data Analyst is an expert in utilizing data to identify trends, solve problems, and create strategies to help businesses succeed. As such, a compelling Senior Data Analyst resume should effectively demonstrate your analytical skills, as well as the leadership experience necessary to be successful in this role.

When writing your Senior Data Analyst resume, here are some essential elements to include:

• Work Experience: Clearly list the positions you’ve held as a Data Analyst, along with the specific data analysis tasks you were responsible for in each role. Be sure to include any relevant projects or initiatives you’ve worked on as well.
• Education: Include your academic credentials, such as degrees and certificates, that demonstrate your expertise in data analysis.
• Technical Skills: Highlight the software programs, coding languages, and other technical tools you’re proficient with.
• Leadership Qualities: Demonstrate how you’ve effectively led teams with your data analysis experience. Showcase how you’ve taken the initiative to identify and solve data-related problems.
• Communication Skills: Show that you can effectively communicate your findings to decision-makers in your organization.
• Problem-Solving: Highlight your ability to glean insights from data and develop strategies to increase efficiency.

By including these essential elements in your Senior Data Analyst resume, you’ll be sure to make an impact and stand out from other applicants.

What is a good summary for a Senior Data Analyst resume?

A great senior data analyst resume summary should highlight the candidate’s experience in gathering, analyzing, and interpreting data to provide insights that inform business decisions. The summary should also mention the candidate’s ability to communicate and collaborate with stakeholders, as well as their understanding of data visualization and data transformation techniques. Additionally, the summary should emphasize the candidate’s experience in developing predictive models and applying machine learning techniques to improve existing processes. By making sure to include these key points, a senior data analyst resume summary should be able to capture the reader’s attention and demonstrate the candidate’s qualifications.

What is a good objective for a Senior Data Analyst resume?

A resume objective is a short, targeted statement that summarizes your career goals and how your skills and experience make you the perfect candidate for the job. For a Senior Data Analyst, a good objective should focus on the ability to utilize analytical and problem-solving skills to find solutions to complex data challenges.

Here are some examples of a good Senior Data Analyst resume objective:

• Highly motivated Senior Data Analyst with 8+ years of experience in data analytics, analysis, and data mining. Seeking to leverage problem-solving and analytical skills to benefit XYZ company.
• Experienced Senior Data Analyst with a background in advanced analytics and data visualization looking for a challenging role at XYZ company.
• Skilled Senior Data Analyst with a proven track record of success in data analysis and reporting. Seeking to use expertise in data modeling and insights to help drive success at XYZ company.
• Results-oriented Senior Data Analyst with a deep understanding of data analysis, data mining, and insights. Eager to apply strong communication and presentation skills to benefit XYZ company.

How do you list Senior Data Analyst skills on a resume?

When writing a resume for a Senior Data Analyst, there are certain skills that employers will expect you to have. Outlining these skills on your resume will demonstrate to the employer that you are qualified for the position. Here are some of the top skills to list on a Senior Data Analyst resume:

• Statistical Analysis: As a Senior Data Analyst, you should be highly proficient in using quantitative methods to collect and analyze data. Be sure to include your experience with statistical techniques like linear and logistic regression, ANOVA, hypothesis testing, and natural language processing.
• Programming: Your resume should also include your familiarity with coding languages like Python, R, Java, SQL, and HTML. Mention any coding certifications or training courses you have taken that demonstrate your programming capabilities.
• Communication: Senior Data Analysts must be able to effectively communicate their findings to colleagues and stakeholders. Include experiences such as giving presentations and writing reports to demonstrate your communication skills.
• Problem Solving: Being able to identify problems and developing solutions to solve them is an important skill for any data analyst. Include examples of how you have used your problem-solving skills to develop innovative solutions.
• Business Acumen: As a Senior Data Analyst, you should understand the business context of your work. Your resume should include your experience in business analysis and your understanding of market research and forecasting.

By highlighting these skills on your resume, you can demonstrate to employers that you have the necessary qualifications for a Senior Data Analyst position.

What skills should I put on my resume for Senior Data Analyst ?

As a Senior Data Analyst, you should showcase the technical and soft skills you have acquired over the course of your career, which will make you a valuable asset for any potential employer.

Below is a list of skills that should be included on your resume for Senior Data Analyst:

• Advanced data analysis skills: You should demonstrate proficiency in data analysis technologies like SAS, SQL, and R. You should also have the ability to interpret complex data sets, dive deep into data structures, and draw meaningful insights.
• Strong communication skills: As a Senior Data Analyst, you’ll need to act as a bridge between the technical and non-technical staff. You should be able to communicate effectively with both parties and make sure that your reports and insights are understood.
• Business acumen: You should be able to understand the business context of the data that you’re analyzing, and how it can be used to make strategic decisions.
• Critical thinking: You should be able to analyze data sets, think outside the box, and come up with creative ways to solve problems.
• Attention to detail: The accuracy of the data is paramount for data analysts. You should be able to identify patterns in the data and detect potential errors.
• Project management: You should be able to manage and prioritize multiple projects, and deliver them on time with minimal supervision.

These are just some of the skills you should include on your resume for Senior Data Analyst. By showcasing these skills, you can show potential employers that you have the technical and soft skills necessary to excel in the role.

Key takeaways for an Senior Data Analyst resume

When crafting your resume as a Senior Data Analyst, your goal should be to showcase the knowledge and skills that make you the ideal candidate for the position. Here are some key takeaways to help you create a winning Senior Data Analyst resume:

• Highlight Your Expertise: Use your resume to show hiring managers that you have the expertise and experience that they are looking for. Feature your experience in data analysis, data mining techniques, data visualization, and/or data interpretation.
• Focus on Your Achievements: It’s important to provide a clear outline of your professional accomplishments and the impact they had on your organization. Think of metrics that demonstrate the value that you added, such as cost savings, increased efficiency, or improved customer satisfaction.
• Utilize the Right Tools: Many Senior Data Analysts use a variety of tools and technologies to perform their job. Make sure to list the tools that you are familiar with, such as Microsoft Excel, Tableau, Power BI, or Python.
• Showcase Your Problem-Solving Skills: As a Senior Data Analyst, you will be responsible for identifying and addressing data-related issues. Showcase your problem-solving skills by highlighting your experience in troubleshooting data-related issues and developing innovative solutions.
• Include Your Soft Skills: Don’t just focus on your technical skills. Your soft skills, such as communication, analytical thinking, and creativity can be just as important to hiring managers. Make sure to emphasize these abilities in your resume.

By following these key takeaways, you’ll be able to craft a resume that will impress hiring managers and increase your chances of landing a Senior Data Analyst position.

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29 Data Analyst Resume Examples for 2024

Data Analyst Resume

• Data Analyst Resumes by Experience
• Data Analyst Resumes by Role
• Writing Your Data Analyst Resume

The number of data analysts is expected to  grow by 25 percent  between 2020 to 2030, coupled with the  increase in pay transparency laws  making this the ideal time to get a data analyst job.

Fun fact: before starting BeamJobs, one of our founders worked as a data analyst for six years. With his guidance, we’ve reviewed many data analyst resumes to figure out what helps data analysts get more interviews.

Building a resume  and  data analyst cover letter  is the hardest part of this process. To inspire you, we chose  29 top data analyst resume samples  for different career stages.

Our data analyst resume examples are proven to help you put your best foot forward to get the job you’ve always wanted in 2024.

or download as PDF

Why this resume works

• Once you know what the employers are looking for, you can include directly applicable keywords and matching language in your work experience bullet points (provided the keywords truly describe you!)
• After you’ve determined the content and matching keywords for your bullet points, add in any quantifiable metrics that can showcase your experience and help prove your merit.

Data Analyst Intern Resume

• If you lack paid work experience in a field, consider it an opportunity to include personal projects on your data analyst intern resume where you demonstrated skills relevant to the position you’re applying to.

Entry-Level Data Analyst Resume

• Unsure how to  make a resume ? No problem! Start by using a  solid resume outline  to help you get a feel for what a resume looks like, then add your experience and skills one at a time.
• The first is to demonstrate programming, testing, modeling, and data visualization competency by building well-designed projects that solve real problems through code.
• The key here isn’t reinventing the wheel but creating something dynamic and unique that can’t be easily replicated with a few Google searches and a video tutorial.
• The second option is to invest time and effort into internships. They’re a fantastic way for an aspiring degree-holder to gain on-the-job experience.
• Some internships require a completed degree before starting. Although this is becoming more uncommon due to online coding trade schools, do some research regarding markets and locations.

Entry-Level Risk Adjustment Data Analyst Resume

• To impress hiring managers, include programming languages you’re familiar with, what you hope to do at your future job, and some of your passions within the field.
• The first is to build well-designed scalable projects that solve real problems through code. So, if you haven’t done any projects, now’s the time to start! Projects are a great way to fill your resume if you don’t have work experience.
• The second option is to get an internship. Some internships require a degree, but online coding trade schools and boot camps are becoming more popular and feasible.

Junior Data Analyst Resume

• Even when a project wasn’t part of a previous job, be as specific as you can by including examples or metrics to show your impact! 
• Ensure that any projects or accomplishments such as internships, classes, or volunteer initiatives, relate directly to the job role. 
• Including a career objective  can also help bulk up your resume with information about what you can offer. 
• Examples and quantifiable metrics of success can make any resume outshine the competition: And they’re extra important for junior data analysts! 
• Since data analysis focuses so heavily on numbers like profits and improvement percentages, include plenty of these to back your credibility. 

Senior Data Analyst Resume

• Highlight a lengthy career in data analyst roles with quantifiable data from multiple sources, jobs, leadership, and mentoring.
• Only include highly relevant ones like Python, SQL, Tableau, and Excel with additional modeling, data visualization, and product analytics keywords.

Senior Insurance Data Analyst Resume

• Including a  resume summary  on your senior insurance data analyst resume helps you highlight your lengthy career with quantifiable data from various sources and can help you land an interview by setting you apart from more novice competition!
• This  resume format  allows the employer to read your work history like an unfolding story, but with the punchline first.
• Only list  skills on your resume  that truly apply to the role at hand; you’ve got limited space—don’t waste it.

Experienced Data Analyst Resume

• The Standout template is basically your best friend since it lets you add your education, skills, and work experience without cramming everything. Cool tones like royal blue further give your experienced data analyst resume the professional yet visually appealing vibe.

HR Data Analyst Resume

• Don’t send your HR data analyst resume out the door without adding hard-hitting numbers like “Formulated 2 advanced Microsoft Excel models… saving $13,941 in extra talent acquisition costs.” This way you’re not just speaking data, you’re displaying its monetary value!

Power BI Data Analyst   Resume

• Take your Power BI data analyst resume up a notch by highlighting any Power BI-based task you’ve led and the kind of impact it created for the company.

Excel Data Analyst   Resume

• Use the Standout template from our library to have enough space for adding all your skills, experience, and education. Include as many skills as you can in your experiences to prove you can always switch from Excel to other tools to extract and refine data.

Python Data Analyst   Resume

• Take a leaf from how William bolds and underlines reducing vehicle downtime by 27% and saving $128K monthly in yearly maintenance costs. Similarly, identifying trends and revenue growth opportunities that increased monthly sales by $101,972 is sure to catch the hiring manager’s eye. You could italicize instead of underlining but let the bold stay.

Data Governance Analyst   Resume

• For your case, achievements that touch on cutting costs (cue:  saving 13% in infrastructure expenses ) and reducing process times (cue:  saving 12 hours per week ) would propel your candidacy to early success.

Data Quality Analyst Resume

• Therefore, to have a soft landing for your application, don’t spare any skills that you feel are relevant to the job—either in your resume or letting an AI cover letter generator have a go at your application. Including your mastery in Talend Data Quality, QuerySurge, Informatica Data Quality, and more would be a great strategy to impress potential employers.

Financial Data Analyst   Resume

• List down the best financial institutions like Citi and Deloitte that you’ve worked for (even for a position as low as an intern or volunteer!) and you’ll be on every employer’s hiring list. It’s also a great idea to list any certifications you hold such as “Chartered Financial Analyst.”

R Data Analyst Resume

• Follow John’s lead and state how you’ve worked with data and specifically (very important!) on R-based frameworks. Keep things simple and vary how you’ve helped each company during your tenure.

Alteryx Data Analyst   Resume

• For instance, rather than simply listing your proficiency in data manipulation, describe how you leveraged your expertise in this area to free up storage space and increase efficiency for the organization.

Big Data Analyst Resume

• Take your big data analyst resume to the next level by demonstrating your prowess in presenting actionable analyses to key organizational stakeholders.

Clinical Data Analyst Resume

• Even a candidate with years of industry experience can optimize their clinical data analyst resume with an additional certification. Make sure recruiters can easily spot that you’re a Certified Clinical Data Analyst (CCDA) to add an extra level of credibility to your background.

Creative Data Analyst Resume

• This will demonstrate to hiring managers that you bring a fresh perspective to the table—always a plus on a creative data analyst resume!

Lead Data Analyst Resume

• Formatting your resume  in reverse-chronological order is always a good way to wow recruiters with your most recent experience and relevant accomplishments. Put your best foot forward!
• Make sure your examples of leading roles are also as well-rounded as possible since this is another quick way to demonstrate how much you’ve learned throughout your career. 
• Since lead data analyst roles are so focused on details and critical thinking, make sure you highlight these areas, too! 
• Use solid, quantifiable metrics like improvement rates and dollar-amount company savings to back up your achievements. 

Healthcare Data Analyst Resume

• For instance, if you’ve completed a B.S. in Health Care Informatics, it means you’ve spent an extensive period of time learning how to analyze and interpret healthcare data and information—which is what most recruiters will be looking for in your healthcare data analyst resume .

Business Data Analyst Resume

• By doing so, you put your most recent accomplishments at the very top of your business data analyst resume —which is where a recruiter or your next potential employer is going to look first.

Marketing Data Analyst Resume

• For instance, if you’ve completed a Professional Certified Marketer (PCM) certification, it’s clear you understand the nuances required to be a marketing professional. Then, you can use the work experience bullet points to focus on the analysis aspect of your role.

AWS Data Analyst Resume

• You only have a couple of sentences to do so, but it’s still a powerful way to tell a recruiter exactly what you bring to the table and what they stand to gain if they hire you.

SQL Data Analyst Resume

• Start by analyzing the requirements in  data analyst job descriptions  to get an idea of what employers require.
• Speak with your current manager if you’re anxious about changing position titles. Always err on the side of caution, and ask for permission instead of forgiveness.

Data Analytics Manager Resume

• Making your resume easy to read  can be as simple as using a  resume template , but it also means  condensing your bullet points as much as you can ,  including metrics  to boost your credibility quickly, and leaving just enough white space to make it a breeze to skim.
• The first is the job description’s list of required skills. The second source is a job board advertising analytics manager roles in a specific geographic location. 
• Both sources give you a general idea of what you need to emphasize in your bullet points and what KPIs to use to complement your experience.

Revenue Reporting Data Analyst Resume

• Your resume should be formulated specifically to target the list of requirements from the company  job description . 
• Use our  resume checker  and a spellcheck extension (like Grammarly) to ensure your resume is error-free.

Data Analyst/Finance Analytics Resume

• Including numbers and percentages is the fastest way to show employers your qualifications. Use metrics to show how you’ve made significant improvements whenever you can.
• Using professional yet stylish  resume templates  and  resume outlines  equips you to add sections specifically for certificates and licenses.
• Don’t be afraid to use a hint of modest color to enhance the overall look of your resume. You’re a pro with personality after all!

Related resume guides

• Data Science Resume
• Financial Analyst
• Computer Science
• Data Engineer

Data Analyst Resume Guide for 2024

According to the  U.S. Bureau of Labor Statistics , the employment of computer and information research scientists (including data analysts) is projected to grow 16 percent from 2018 to 2028. This is much faster than the average for other jobs!

Due to the high demand and high wages, it makes sense that people are flocking to apply for data analyst roles.

But that doesn’t mean you should be discouraged. Applying online to jobs can feel like applying in a black hole, and we know it sucks.  It took one of our founders 77 job applications  before he landed his first data analyst job at Geico, and the next job was much easier to get.

One issue with applying for data analytics roles is that these titles are not standardized across different companies. At one company, data analysts might spend their time building reports in Tableau, while at another, they might be writing machine learning models for production.

Because of this variability, it can be tough to be sure to include the correct information in your data analytics resume. With this guide, you’ll put your best foot forward, no matter which data analyst roles you’re seeking!

Show off your data analyst skills

First, you need to show you have the right abilities for the job! This means you need to accomplish two goals with the  skills section of your data analyst resume . First, you have to be able to get past the automatic keyword filters in the applicant tracking system (ATS), which companies use to filter applicants. Next, you want to demonstrate your technical proficiency to the person reviewing your resume.

If you’re unsure which skills to include, we analyzed the data to learn  which skills are most in demand for companies hiring data analysts .

These two goals are, unfortunately, mostly in opposition to each other. If your goal was to just get past the ATS, you’d list every skill to get your foot in the door:

Bad — avoid a long list of generic skills

The problem? This method is a big red flag to technical hiring managers. You should only include skills you’d be comfortable discussing in your  data analyst interview . Plus, your  skills section shouldn’t take up more than 20 percent  of the page.

Any reasonable employer won’t expect you to know SAS, R,  and  Python. Instead, just list the technical skills that you’ve coded in before. And avoid including a skill like “data mining” or “data analysis” since a technical hiring manager knows these are just blanket terms that don’t mean much. Instead of “data mining,” list actual techniques you’ve used, like “decision trees” or “logistic regressions.”

But even when narrowing it down, sometimes your skills list looks cluttered and hard to read. Never fear; there are multiple ways to organize your skills section! For starters, you can list your skills by how proficient you are with them (“Advanced” vs. “Familiar,” for example). Alternatively, you can list your skills by skill type. You can even mention the years of experience you have with each tool.

For programming languages, mention the libraries and frameworks you use for data visualization and manipulation in that programming language.

Good—specific skills and modeling techniques

Your data analyst objective

Most of the time, you don’t need to include a  resume objective  or  resume summary ; a mistake many data analysts make. If a resume summary or objective doesn’t add value to your application, it’s okay to leave it out.

Here’s a sample data analyst resume objective that you would want to leave off of your resume:

Bad—uninformative resume objective

Why leave this off? It’s redundant. Suppose you already demonstrate in your resume that you used tools like Python and SQL to turn data into actionable insights. In that case, your objective doesn’t tell the person reviewing your resume any new information.

When to include a resume objective

• You’re undergoing a career change. You can say something like, “After 4 years of working in operations, I am now looking to leverage my expertise in turning data into insights as a data analyst.”
• You have a specific interest in a given role or company that makes you an especially strong candidate. For example, “Reading Match.com’s data blog ignited my pursuit of a career in data analytics, and I want to further contribute to the data-driven culture at the company.”

Summaries are similar, but they’re for candidates with over 10 years of experience and can include more personal achievements. There isn’t much difference between a resume summary or an objective; all you need to know is when you should include them.

Data analyst resume format

Here are some quick tips for formatting your data analytics resume:

• Keep it to one page.
• Break up bullet points into small, consumable pieces of information.
• Don’t refer to yourself with “I” or “we,” as it takes up room and looks unprofessional.
• Double, triple, and quadruple-check your grammar and spelling. One error can send your resume into the “no” pile!
• Each bullet point on your resume should be a self-contained, complete thought.

When a hiring manager reviews 50+ resumes for a given role, they quickly look for reasons to say “no.” By using these  resume-formatting tips , you make it easier for the hiring manager to see your worth and ask you for an interview, getting you one step closer to a job. 

Contact information

Of all the places to make an error, your contact information is the  worst  place to have it happen. One of our team members recounted their early days out of college as a data analyst. When they were applying for jobs, they accidentally wrote the wrong email address on their resume for seven different positions.

Even if they were perfectly qualified for the role, there was no way to contact them because of a minor mistake. So believe us when we say you need to  triple-check this section for any spelling, grammar, or link errors .

As part of your contact information, you should include your name and the role you’re applying for (even if it’s not your current role).

You don’t need to include your full address in this section, but you should list your city and zip code. You also need your phone number just in case your employer prefers that method.

Finally, include a link to your LinkedIn profile and anything else that might convey why you’re a great data analyst. If you have an active Github, include a link to that. If you do a lot of Kaggle contests, include a link to your profile. Have a personal blog where you talk about election data? Be sure to include a link.

Data analyst projects for your resume

If you’re entry-level and looking for your first full-time role, including projects on your data analyst resume is an absolute must. However, the more work experience you get, the more projects should become less critical. By the time you have four-plus years of experience in the field, you should only include a project of which you’re exceptionally proud.

What projects should you list? Anything where you identified (or were given) a problem and you used data to come up with an answer to that problem. It’s okay if it’s a class project, but it’s even better if you took the initiative yourself.

If you don’t have any such projects, now is the time to work on some. Do you have a question you’ve never answered? An experiment you’ve been longing to try? Think of a way to gather and analyze data to sate your curiosity.

Here’s an example: one of our founders had a hunch that the major job boards (Indeed, Glassdoor, and LinkedIn) essentially had the same jobs for data science roles. So, he manually collected data, analyzed it, and wrote about it to determine the  best job board for data scientists .

The projects you include don’t need to be exhaustive or ground-breaking. Employers just want to see that you can ask a question, use data to answer it, and present your findings reasonably and clearly.

Good—show you can answer your own questions with data

When talking about your projects, here’s how you should frame what you did:

• Clearly state the question you were answering or the problem you were trying to solve
• Show what tools or languages you used to solve the problem
• State the impact of the work you did

Your projects section is also an opportunity to provide more context around the programming languages and libraries you listed in your “skills” section. 

Like the “projects” section, the education section of your resume will be longer for entry-level data analysts relative to more experienced data analysts. You’ll want to include relevant courses you took in school related to data analytics for entry-level data analysts.

Courses relevant to data analytics are any mathematics, statistics, programming, and economics classes you took. To be an effective data analyst, you need to apply the principles you learned in these classes to real-world problems and datasets.

For entry-level roles, include relevant classes you took in school

Regardless of your experience level, you should always mention the school you attended, what you majored in (including minors or certifications), and when you graduated. This would also be the place to list any boot camps or relevant online courses you may have taken in the field.

If your background is in academia, you can also list any publications you may have co-authored. Be sure to include the title of the magazine and a link to allow the hiring manager to read further if they’re interested.

Only mention your GPA on your resume if it’s something you want to highlight—generally, only list your GPA if you’re entry-level and obtained anything above a 3.0.

Work experience

You analyze data for a living, so you know that numbers count when it comes to information. So when you’re talking about your work experience, your goal should be to highlight your accomplishments using numbers and estimates.

The formula for talking about work experience

“Specific contribution to project mentioning specific tools and skills”

“quantitative impact of the project”

“Performed a customer cohort analysis using SQL and Excel and recommended an email campaign for one customer segment”

“that lifted monthly retention by 10%”

Enter your text here…

When discussing your work, especially if it was a team project, emphasize your specific contributions. For example, you may have made a product recommendation based on a previous analysis. You’d want to talk about that particular recommendation on your resume instead of the built feature.

When talking about the quantitative impact, it’s okay to talk about the project as a whole. Following the example above, it’d be impossible to tease out the value of your product recommendation versus the engineer’s impact who built the feature since it’s a team effort. You’d say the feature had a revenue impact of $X on your resume.

Data analysts work across many different teams and projects in a company, so it’s not always easy to tie your work to a revenue impact. Still, try estimating your contributions using metrics to make your resume stand out.

These can be very rough estimates; you just want to make it clear that you’ve contributed to positive outcomes for the businesses where you worked.

Ways to quantify the impact of your analytics work

• “Used Python and SQL to determine a specific change in the landing page, resulting in a 10% boost in free trial activation rate”
• “Streamlined and automated a key business report in Tableau, saving the team 10 hours of reporting each week”
• “Used SQL and Excel to recommend ending contracts with worst-performing vendors, resulting in a costs savings of $100,000 annually”
• “Built data visualizations in Excel to demonstrate the efficacy of marketing plan, resulting in the close of a $1.3M Series A”
• “Determined through analysis in Python that emailing customers who had been inactive for 7 days resulted in a retention improvement of 7 basis points”
• “Identified procedural areas of improvement in hiring data to improve the time-to-hire for key roles by 11 days”
• “Used SQL and Excel to identify common complaints amongst new customers, leading to changes that improved new customer satisfaction by 14%”

When formatting your work experience, always list your most recent work at the top of your resume and list your other positions in reverse-chronological order.

Just to hammer home our point even further, here’s an example of the same work experience. One is stated in a quantitative impact, and one is not. 

Bad—no quantitative impact

Good—quantitative impact

Tailor your resume for each job

For each role to which you apply,  make minor edits to your resume  based on the  data analyst job description . Fortunately, you don’t have to completely rewrite your resume; just a few tweaks will do.

For example, let’s say you’ve done projects in both Python and R, and your resume heavily leans into your Python experience. If you apply to a job that mentions R, you should change your resume to discuss your R experience.

Similarly, if you have specific projects that relate to the job you’re applying for, include those projects. If you’re applying for a marketing data analyst role and have experience building marketing mix models, your application will become significantly stronger by mentioning those mix models.

Let’s say you’re applying to this job:

This seems like a heavy data visualization role. Instead of mentioning predictive modeling, talk extensively about your experience building robust data visualization in Tableau.

Change this:

How to Write an Effective Data Analyst Resume

Here are the major takeaways you should keep in mind when  writing a professional resume :

• Keep it to one page and  proofread, proofread, proofread .
• Otherwise, don’t let your education section take up a lot of space.
• You don’t need a summary or objective section on your resume unless you’re undergoing a career change or have over 10 years of experience.
• Only include skills on your resume for which you’d be comfortable being interviewed.
• Mention your specific contributions and quantify the overall project’s impact on the business.

By following this guide, you’ll be able to quickly and convincingly make the case that you’re a great fit for the data analyst role for which you’re applying. 

Applying for jobs isn’t easy, but you’ve taken a huge first step toward landing that dream job. Now all that’s left is to write,  double-check your resume  for errors, and submit it to your dream job!

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Senior Data Analyst- resume examples for 2024

A senior data analyst- resume should showcase a strong ability to analyze data and create visualizations to communicate insights effectively. This includes being proficient in tools like Power BI, SAS, and Tableau. According to Robert Hyers FASM , George I. Alden Professor and Head at Worcester Polytechnic Institute, "Be thoughtful about how to add value for your employer and for their customers. Be part of the solution." A strong analytical mind and interpersonal skills are also essential for success in this role.

Senior Data Analyst- resume example

How to format your senior data analyst- resume:.

• Use the job title 'Senior Data Analyst' on your resume to match your application for the role.
• Focus your work experience on specific achievements that demonstrate your expertise, such as developing advanced Tableau visualization techniques or creating VBA scripts to automate reports.
• Recruiters and hiring managers recommend limiting your resume to one page, focusing on the most relevant and impressive accomplishments for the Senior Data Analyst position.

Choose from 10+ customizable senior data analyst- resume templates

Choose from a variety of easy-to-use senior data analyst- resume templates and get expert advice from Zippia’s AI resume writer along the way. Using pre-approved templates, you can rest assured that the structure and format of your senior data analyst- resume is top notch. Choose a template with the colors, fonts & text sizes that are appropriate for your industry.

Senior Data Analyst- resume format and sections

1. add contact information to your senior data analyst- resume.

Senior Data Analyst- Resume Contact Information Example # 1

Dhruv Johnson

[email protected] | 333-111-2222 | www.linkedin.com/in/dhruv-johnson

2. Add relevant education to your senior data analyst- resume

Your resume's education section should include:

• The name of your school
• The date you graduated ( Month, Year or Year are both appropriate)
• The name of your degree

If you graduated more than 15 years ago, you should consider dropping your graduation date to avoid age discrimination.

Optional subsections for your education section include:

• Academic awards (Dean's List, Latin honors, etc. )
• GPA (if you're a recent graduate and your GPA was 3.5+)
• Extra certifications
• Academic projects (thesis, dissertation, etc. )

Other tips to consider when writing your education section include:

• If you're a recent graduate, you might opt to place your education section above your experience section
• The more work experience you get, the shorter your education section should be
• List your education in reverse chronological order, with your most recent and high-ranking degrees first
• If you haven't graduated yet, you can include "Expected graduation date" to the entry for that school

Check More About Senior Data Analyst- Education

Senior Data Analyst- Resume Relevant Education Example # 1

Bachelor's Degree In Business 1998 - 2001

Ashford University San Diego, CA

Senior Data Analyst- Resume Relevant Education Example # 2

Bachelor's Degree In Accounting 2008 - 2011

University of Maryland - College Park College Park, MD

3. Next, create a senior data analyst- skills section on your resume

Your resume's skills section should include the most important keywords from the job description, as long as you actually have those skills. If you haven't started your job search yet, you can look over resumes to get an idea of what skills are the most important.

Here are some tips to keep in mind when writing your resume's skills section:

• Include 6-12 skills, in bullet point form
• List mostly hard skills ; soft skills are hard to test
• Emphasize the skills that are most important for the job

Hard skills are generally more important to hiring managers because they relate to on-the-job knowledge and specific experience with a certain technology or process.

Soft skills are also valuable, as they're highly transferable and make you a great person to work alongside, but they're impossible to prove on a resume.

Example of skills to include on an senior data analyst- resume

The dashboard is a data management tool used for business intelligence. Dashboards, store, organize and display the scattered data in one system providing easy access to information whenever required. The data is displayed using advanced data visualization techniques, allowing users to understand the intricate patterns in their data. Dashboards make it easier to draw parallels between different data metrics and help in the identification of data trends.

SAS stands for Statistical Analysis System which is a Statistical Software designed by SAS institute. This software enables users to perform advanced analytics and queries related to data analytics and predictive analysis. It can retrieve data from different sources and perform statistical analysis on it.

Hadoop is an open-source software and procedures framework that is free for anyone to use on the internet. Hadoop aids in big data operations. It allows massive data storage, applications to be run on commodity hardware, and can easily manage to run various tasks occurring at the same time.

Java is a widely-known programming language that was invented in 1995 and is owned by Oracle. It is a server-side language that was created to let app developers "write once, run anywhere". It is easy and simple to learn and use and is powerful, fast, and secure. This object-oriented programming language lets the code be reused that automatically lowers the development cost. Java is specially used for android apps, web and application servers, games, database connections, etc. This programming language is closely related to C++ making it easier for the users to switch between the two.

Data warehouse, often abbreviated as either DW or DWH is a system used in computing for data analysis as well reporting. The DW is also considered to be an integral component of business intelligence as they also provide storage facilities for both real-time and historical data. ETL and ELT are the two driving forces behind a data warehouse system.

Data governance is an assortment of cycles, jobs, arrangements, principles, and measurements that guarantee the successful and productive utilization of data in empowering an association to accomplish its objectives. Information administration characterizes who can make a what move, upon what information, in what circumstances, utilizing what strategies

Top Skills for a Senior Data Analyst-

• Data Analysis , 10.7%
• Power Bi , 9.7%
• Visualization , 9.2%
• Dashboards , 5.8%
• Other Skills , 64.6%

4. List your senior data analyst- experience

The most important part of any resume for a senior data analyst- is the experience section. Recruiters and hiring managers expect to see your experience listed in reverse chronological order, meaning that you should begin with your most recent experience and then work backwards.

Don't just list your job duties below each job entry. Instead, make sure most of your bullet points discuss impressive achievements from your past positions. Whenever you can, use numbers to contextualize your accomplishments for the hiring manager reading your resume.

It's okay if you can't include exact percentages or dollar figures. There's a big difference even between saying "Managed a team of senior data analysts" and "Managed a team of 6 senior data analysts over a 9-month project. "

Most importantly, make sure that the experience you include is relevant to the job you're applying for. Use the job description to ensure that each bullet point on your resume is appropriate and helpful.

• Coordinated new account setup for Sharepoint and Pilgrim Smartsolve.
• Enforced business rules using PL/SQL in Database Triggers/Stored Procedures/Functions.
• Managed and analyzed SKU assortments for Family Planning Category and presented assortment suggestions to Supervalu for planograms.
• Created new JCL jobs and COBOL programs to manage tax system outputs Successfully completed an array of business critical projects.
• Produced application architecture, high level design and integration design artifacts by collaborating within organization and external vendors.
• Used SQL for Clarify data manipulation in the custom application.
• Examined requirements for analytics and documented business rules.
• Tested SQL Server upgrades, implemented the upgrades to the servers, and migrated SQL Server version 7.0 to 2000.
• Established strong customer rapport and facilitated twice weekly meetings to discuss increasing their workload migration within the cloud.
• Installed the SPSS server and client software to connect to the analytic node to retrieve the Hadoop data.

5. Highlight senior data analyst- certifications on your resume

Specific senior data analyst- certifications can be a powerful tool to show employers you've developed the appropriate skills.

If you have any of these certifications, make sure to put them on your senior data analyst- resume:

• Certified Data Management Professional - Data Management (CDP-DM)
• Software Engineering Master Certification (SEMC)
• Associate - Data Science Version 2.0
• Google Data Analytics Professional Certificate

6. Finally, add an senior data analyst- resume summary or objective statement

A resume summary statement consists of 1-3 sentences at the top of your senior data analyst- resume that quickly summarizes who you are and what you have to offer. The summary statement should include your job title, years of experience (if it's 3+), and an impressive accomplishment, if you have space for it.

Remember to emphasize skills and experiences that feature in the job description.

Common senior data analyst- resume skills

• Data Analysis
• Visualization
• Statistical Analysis
• Data Warehouse
• Excellent Interpersonal
• Data Governance
• Strong Analytical
• Digital Marketing
• Excellent Organizational
• Data Integrity
• Pivot Tables
• Business Processes
• Econometrics
• Data Warehousing
• Data Extraction
• Informatica
• Client Facing
• Database Objects
• Business Rules
• Data Validation
• Data Elements
• Physical Data Models
• Technical Specifications

Senior Data Analyst- Jobs

Links to help optimize your senior data analyst- resume.

• How To Write A Resume
• List Of Skills For Your Resume
• How To Write A Resume Summary Statement
• Action Words For Your Resume
• How To List References On Your Resume

Updated June 25, 2024

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

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• Senior Data Analyst- Resume

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Senior Data Analyst Resume Sample

Home » IT Resume Samples » Senior Data Analyst Resume Sample

Are you a  Senior Data Analyst  by profession and looking for a career change? We have good news for you! use our job-winning professional  Senior Data Analyst Resume Sample  template. You don’t have to start writing from scratch. Just click “Edit CV” and modify it with your details. Update the template fonts and colors to have the best chance of landing your dream job. Find more  Resume Templates.

Ryan Brandon

Senior data analyst.

Professional with more than 8+ years of Data Analytics experience. Worked extensively in Development Regular & Ad-hoc Reports and maintenance projects of Power BI. 

• Experience in preparing KPIs and Power BI Dashboard.
• Quick learner and a good team player.
• Possess good analytical and problem-solving
• Preparing reports on sales performance, promotions, pricing, cost, New line setup and markdowns.
• Microsoft Excel
• Microstartegy

Work Experience

Data analyst.

• Worked extensively in Development Reports and maintenance project of Power BI. 
• Handling BAU weekly/monthly production process for multiple countries and  perform trend ability checks n markets to check the trends of markets previous year by checking and analyzing sample stores count for different periods for the corresponding market. Finding data quality errors and sending the same to data audit people to correct errors.
• Created Power BI dashboard and have to provide insight from the dashboard.
• Communication of findings to the Project leaders and Business leaders, and raising issues to resolve, to ensure efficient closure of validation of simulation and universe update.

Technical Process Executive

• Automating the reports
• Updating policy information on server
• Quality check on weekly and montly basis
• Backup the policy information 
• Providing reports to the senior management team

Console Monitoring

• Checking CPU performance 
• Create/delete the user ID and grant/revoke an access
• Assisting users on synatx error
• Archieve the server information

Bachelor of Engineering, Computer Science

New store’s sales performance handling.

Extracting data from different sources and comparing last year to this year on sales value, volume, profit and margin providing insights to increase the sales on store level by publishing the report or dashboard to senior management team, stake holders and store directors.

Career Expert Tips:

• Always make sure you choose the perfect resume format to suit your professional experience.
• Ensure that you know how to write a resume in a way that highlights your competencies.
• Check the expert curated popular good CV and resume examples

What is the Role of a Senior Data Analyst?

In the era of data-driven decision-making, a Senior Data Analyst plays a crucial role in extracting meaningful insights from raw data to help organizations make informed choices. This role involves a deep dive into data, exploring its depths, and surfacing with valuable knowledge that can steer the business towards success. A Senior Data Analyst not only crunches numbers but also interprets them, translating complex datasets into understandable and actionable information.

They work closely with various stakeholders, ensuring that the data’s story is told effectively, influencing strategies and driving improvements. Their analytical prowess helps in identifying trends, patterns, and anomalies, which are pivotal in shaping business strategies and solving complex problems.

What are the Senior Data Analyst Job Requirements?

Embarking on the journey to become a Senior Data Analyst requires a blend of education, experience, and skills. Here’s a closer look at the essential requirements:

• A Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, or a related field, laying the foundation for a career in data analysis.
• Profound knowledge of statistical tools and programming languages such as SQL, R, or Python, essential for diving into the world of data.
• Experience in data cleaning, visualization, and reporting, showcasing the ability to transform raw data into meaningful insights.
• Strong communication skills, enabling the translation of complex data findings into understandable and actionable insights for non-technical stakeholders.
• A curious and analytical mind, driving the exploration of data to uncover hidden patterns and trends.

Additional certifications in data analysis or related fields can further enhance your profile and keep you abreast of the latest industry trends and best practices.

What are the Responsibilities of a Senior Data Analyst?

The responsibilities of a Senior Data Analyst are diverse and multifaceted, involving a mix of technical, analytical, and communication tasks. Here’s a snapshot of what this role entails:

• Collecting and interpreting data from multiple sources, ensuring accuracy and reliability.
• Developing and implementing data analyses, data collection systems, and other strategies that optimize statistical efficiency and quality.
• Identifying patterns and trends in data sets, translating findings into actionable business insights.
• Working alongside teams within the business or the management team to establish business needs.
• Creating data dashboards, graphs, and visualizations, providing a clear picture of the business landscape.
• Addressing data-related problems in regards to systems integration, compatibility, and multiple-platform integration.

Each responsibility is a step towards helping the organization make data-driven decisions, ultimately contributing to its success.

Senior Data Analyst Resume Writing Tips

Creating a standout resume is your ticket to landing that dream role as a Senior Data Analyst. Here are some tips to help you craft a resume that tells your story effectively:

• Highlight your experience in data analysis, showcasing specific projects where you extracted meaningful insights from data.
• Detail your proficiency in statistical tools and programming languages, demonstrating your technical expertise.
• Include any certifications or additional training you’ve completed, showing your commitment to continuous learning.
• Don’t forget to mention your communication skills, illustrating your ability to translate complex data findings into understandable insights.
• Personalize your resume for the specific role, aligning your skills and experiences with the job requirements.

Remember, your resume is your personal brand statement, make it count!

Senior Data Analyst Resume Summary Examples

Your resume summary is like the book cover of your career story. It should captivate the reader and give them a glimpse of what’s inside. Here are some examples to get you started:

• “Detail-oriented Senior Data Analyst with 8+ years of experience specializing in interpreting and analyzing data to drive growth for a diverse range of companies. Proficient in statistical tools and programming languages.”
• “Results-driven Senior Data Analyst with a knack for unraveling complex data sets, translating findings into actionable business insights. Adept at creating data visualizations and dashboards.”
• “Analytical Senior Data Analyst with a passion for turning data into information, information into insight, and insight into business decisions. Skilled in SQL, Python, and data visualization tools.”

Each summary should be a reflection of your unique skills, experiences, and value proposition.

Create a Strong Experience Section for Your Senior Data Analyst Resume

The experience section is the heart of your resume. It’s where you get to showcase your journey, your achievements, and your learnings. Here’s how you can make

• Detail specific projects where you applied your data analysis skills to extract meaningful insights.
• Showcase your proficiency in using statistical tools and programming languages, highlighting any advanced techniques you’ve applied.
• Don’t shy away from mentioning challenges you’ve overcome, problems you’ve solved, and the impact of your work on the business.
• Include any cross-functional collaborations, showcasing your ability to work with diverse teams and stakeholders.

Remember, each experience is a chapter in your career story, make it compelling!

Sample Education Section for Your Senior Data Analyst Resume

Your educational background lays the foundation for your career in data analysis. Here’s how you can list it on your resume:

• M.Sc. in Statistics, Stanford University, Stanford, CA, 2018
• B.Sc. in Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 2016
• Certified Data Analyst, Data Science Certification Institute, 2019

Each degree and certification is a building block in your career, showcasing your knowledge and expertise.

Senior Data Analyst Skills for Your Resume

As a Senior Data Analyst, your skillset is a diverse palette of technical, analytical, and soft skills. Here’s how you can list them:

Soft Skills:

• Communication
• Problem Solving
• Attention to Detail
• Adaptability

Hard Skills:

• Data Collection and Analysis
• Statistical Tools (R, Python, SQL)
• Data Visualization
• Machine Learning
• Database Management

Each skill is a brushstroke, painting a picture of your capabilities and expertise.

Most Common Mistakes to Avoid When Writing a Senior Data Analyst Resume

Avoiding common mistakes can be the difference between your resume landing in the ‘yes’ pile or the ‘no’ pile. Here are some pitfalls to steer clear of:

• Using a generic resume for every job application, missing the opportunity to align your resume with the specific role.
• Focusing solely on job duties and not highlighting your achievements and the impact of your work.
• Ignoring the importance of a well-crafted cover letter that complements your resume.
• Overloading your resume with technical jargon, making it difficult for non-technical stakeholders to understand.
• Not proofreading your resume, leaving room for typos and grammatical errors that can tarnish your professional image.

Each mistake is a hurdle, overcome them to create a flawless resume.

Key Takeaways for Your Senior Data Analyst Resume

As we wrap up, let’s revisit the essential elements to include in your Senior Data Analyst resume:

• Showcase your journey in data analysis, highlighting specific projects and achievements.
• Detail your technical proficiency, focusing on your skills in statistical tools and programming languages.
• Include any additional certifications or training, demonstrating your commitment to learning and staying updated.
• Highlight your communication skills, showcasing your ability to translate complex data findings into understandable insights.

Finally, feel free to utilize resources like AI Resume Builder , Resume Design , Resume Samples , Resume Examples , Resume Skills , Resume Help , Resume Synonyms , and Job Responsibilities to create a standout application and prepare for the Senior Data Analyst job interview .

With these insights and resources at your disposal, you are well-equipped to craft a resume that reflects your unique skills, experiences, and aspirations. Best of luck on your journey to becoming a Senior Data Analyst!

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Privacy overview.

Senior Data Analyst Resume Samples

Senior data analysts are professionals who specialize in collecting, organizing and analyzing data for the company. The highlighting responsibilities that are taken up by senior data analysts are gathering, extracting, manipulating, analyzing and modeling data by using statistical and analytical tools, providing database maintenance and other developments and creating ad hoc reports and ensuring data accuracy. Additionally, these analysts design, code, debug, test and support server-based applications.

The senior data analyst should demonstrate an ability to troubleshoot, create and enhance company’s data loadings, they should additionally have a clear understanding of IT business systems, data warehousing, general ledger management and have strong working knowledge of Oracle business intelligence or Tableau or similar tools. Even though a Master’s degree will highlight a Senior Data Analyst Resume , a Degree in Data Science, IT, Computer science or information systems is considered as the minimum qualification for this job role.

• Resume Samples
• Senior Data Analyst

Senior Data Analyst Resume

Summary : Highly qualified Senior Data Analyst with experience in the industry. Enjoy creative problem solving and getting exposure on multiple projects, and excel in the collaborative environment on which your company prides itself.

Skills : Tableau, Visio, Business Intelligence, Business Objects,.

Description :

• Database Analysis Created advanced relational database Visual Basic and MS Access formulas such as; Joins, Unions, and ODBC.
• Maintained, reviewed, imported, exported, cleaned, and created sales and financial relational databases Developed data requirements to support business finance needs with I/T to defined changes.
• Utilized several financial reporting tools to analyze data and present reports and recommendations including; Brio, Essbase, MS Excel, Hyperion Essbase, and Impromptu Built financial relational database by identifying sources of information, assembling, verifying, and backing up finance and sales data.
• Data Mining Uncovered patterns in data samples through the use of representative and non-representative samples indicative of the domain and of the whole population by verifying and validating patterns of other samples of financial and sales data.
• Identified trends within financial data through the use of sophisticated algorithms, to identify key attributes of processes and target opportunities.
• Extracted hidden patterns of financial data used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery.
• Performed Data Clustering to automatically discover the segments or groups within a customer data set.
• Database Design Developed and managed dashboard metrics for the company to improve management decision-making and performance.

Junior/Senior Data Analyst Resume

Headline : A self-starter having a multi-discipline background emphasizing data analyzing, data security, quality control, database extractions and loads, quality assurance, data mining and software testing.

Skills : Data Analysis, Data Mining, Data Entry, Excel, Microsoft Office, Power Point, Process Improvement, Problem Solving, Data Warehousing, Databases.

• Maintaining and monitoring processed records for reference of historical and real time Bathymetric Nautical Planning Charts (BNPC), utilizing NAVOCEANO software and tools.
• Work with programmers on testing new beta-type software, tools and variables while maintaining quality assurance of the database production.
• Merge depth layers into real data that were created using mathematical formulas to give a number value within a specific error percentile for support of war fighters and other functions.
• Build and subset various databases using Graphical User Interface (GUI) and command scripts for ingest and extraction of sensitive bathymetric and hydrographic data.
• Examine, evaluate and compare datasets for quality and precision.
• Ingest, integrate and merge cartographic, hydrographic, geospatial and bathymetric data before inclusion into a gridded database to create seamless digital interface of the seafloor.
• Coordinate and execute special supplemental database deliveries to customers, agencies and other scientific communities.

Senior Data Analyst/Executive Resume

Summary : Articulate, passionate and visionary Senior Business Analyst who is a leader of positive change. Thrives on the ability to understand the business values and translate them into technical deliverables. Enabling teams and organizations to embrace the change that they need in order to achieve the results that they want.

Skills : Business Analysis, Business Intelligence, Project Management, Visio, Change Management, Facilitation, Requirements Analysis, Requirements Gathering, Requirements Management, Usability Testing, Use Cases, Relationship Management, Team Leadership, Team Building, Team Development.

• Managed and coordinated BI and reporting and process redesign initiatives to support financial, lending, accounting and remarketing services.
• Elicited, analyzed and validated requirements to identify BI redesign initiatives and demonstrated how technology solutions supported the redesigned business process flow.
• Operated as change champion through education, leading change, and influencing positive outcomes.
• Focal point of contact for addressing the reporting needs for Call Centers' executive management.
• Provided regular, transparent project status updates.
• Led data integration and migration efforts of merging business applications and data repositories between MarketWise and JM Family Enterprises Identified and documented opportunities for new technology solutions to support reengineered business processes through interactive JAD sessions; provided recommendations for technology selection.
• Created new reporting solutions, introduced dashboard presentation technology merging business process rules with workforce management reporting, improving call center workflow efficiency.
• Planned and successfully managed multiple application and reporting upgrade migration projects increasing billing and collection department efficiency by 39% over a 14 month period.

Senior Data Analyst/Consultant Resume

Headline : Data Science professional with 3+ years of experience in solving business problems across domains and industries Practiced in clarifying business requirements, performing analysis between goals and existing procedures, and designing process improvements to increase productivity and reduce costs Proven ability in moving up the learning curve quickly, with solid academic and employment achievements.

Skills : Microsoft Office.

• Identified data discrepancies in key business reports that were leading to incorrect reporting of crucial financial data.
• Worked with engineers to fix data tables and queries to eliminate discrepancies.
• Introduced new and formal technical requirements and QA documents to define formal processes for quality assurance, business task initiation, and completion.
• Held full responsibility for the research, troubleshooting, and utilization of the Omniture web analytics tool and its tracking and reporting functions to ensure all business reporting data elements were accurate.
• Managed Business Objects user account administration and maintenance.
• Performed quality assurance testing, created test cases and test plans for data warehouse projects and QA testing.
• Demonstrated understanding of data requirements and the StubHub organization to document requirements for data warehouse projects including a key marketing project to gauge marketing channel performance.

Senior Data Analyst III Resume

Headline : Able to identify problems and implement corrective processes. Strong communication, interpersonal, and presentation skills. Track record for meeting timelines and exceeding expectations.

Skills : Fluent In Both Written And Spoken Spanish - Multi-Functional Work Station And ArcGIS - Microsoft Professional Office Applications.

• Responsible for the day-to-day analytical operations generating close reports with the Navy and civilian personnel, capturing scope effects safely, in a timely manner with successful accomplishment under contract requirements.
• Act as the liaison representative between government, military, and civilian contracted personnel.
• Analyze, collect, record, interpret, and maintain data related to MSC vessel types, force protection, and various special missions and programs.
• Conduct daily tasks to provide advice and coordinate the execution of special projects related to data collection and analysis, ensuring the completeness and consistency of data.
• Prepare briefings or support documents related to the specific issue, researching the issue to identify errors and/or omissions, and the proposal of recommendations.
• Perform data analysis including; data collection in gathering, maintaining, and providing monthly and cumulative tracking of all ship-related data.
• Conduct analyses and investigations of raw data collected by applying analytical methods from mathematics, science, and engineering to elaborate, advice and provide insight into probable effects of alternative solutions to problems.

Senior Data Analyst II Resume

Headline : Senior Data Analyst is responsible for providing data analysis and reporting to senior management. This includes preparing reports, analyzing and presenting data to senior management, as well as training and mentoring junior analysts.

Skills : R, SQL, MATLAB, SPSS.

• Fostered the utilization of SQL and Excel in managing all data transformation, mappings, and migrations for multiple clients.
• Secured additional information from numerous linked servers connected to SQL and Oracles tables using queries.
• Prepared and presented SQL Server Reporting Services (SSRS)/Hyperion reports, which detailed risk characteristics and location.
• Coordinated with the Information Technology department with regard to documented business designs and unit test plans in compliance with Sarbanes-Oxley (SOX).
• Administered the National Council on Compensation Insurance (NCCI) regulatory and compliance reporting.
• Made substantial contribution in preparing and presenting reports and analysis, predictive modeling and other data mining results using SSIS, Excel and Access applications.
• Reliably aided the Underwriting, Actuarial, and Finance and Claims departments with innovative business intelligence and statistical analysis.
• Defined a large list of related variables using mining techniques including principle components and classification of large datasets to develop business judgment using SQL Server Integration Services (SSIS) and Excel charts/pivot tables.

Senior Data Analyst I Resume

Summary : Team Lead and Technical Analyst working with Accenture for 6+ years, handling varied roles and responsibilities in the organizational delivery model.

Skills : SAS, R, SQL, Excel, Splunk, Tableau, SSIS, SSAS.

• Established the creation of metrics, reporting and repeatable processes that provided the basis for robust long-term performance monitoring, cost modeling and trend management of Neustar's Operational Infrastructure and Service Quality.
• Identified and validated data sources and educated employees throughout the company on how to leverage the information to assist making decisions and understand service health and capacity.
• Led the design and development of analytical projects to understand key business behaviors that drive customer satisfaction, goodwill, and engagement.
• Managed the collection, analysis and communication of insights to enable the business to make informed decisions, forecast implications of initiatives undertaken and monitor changes introduced to enhance client experience.
• Performed Operational Cost analysis to improve operational efficiency and in turn driving revenue growth.
• Provided monthly reporting to senior leadership on key performance indicators (KPI) and SLA statistics.
• Provided actionable audience specific recommendations.
• Worked cross functionally as part of larger project teams to deliver against corporate scorecard initiatives.

Summary : Creating and maintaining data marts and semantic layers to fulfill the business' need for data and information in the healthcare, manufacturing, mortgage and finance industries. Twelve years of professional experience designing comprehensive Business Intelligence systems with OLAP, reporting and dash-boarding capabilities.

Skills : BI, Data Analysis, Data Analysis, Database Management, Databases, SQL, Data Modeling, SQL Server, DAX.

• Responsible for the design and implementation of a Business Intelligence solution for the entire company, including a data warehouse, automated reports and user interface for ad hoc reports and analytics.
• Responsible for the data analysis and business analysis to enable the creation, enhancement, and maintenance of the data warehouse.
• Complex troubleshooting and extensive interviewing of the business users and subject matter experts.
• Responsible for health care informatics, including calculation of claims lag triangle, incurred but not realized (IBNR) amounts, utilization rates, disease management rates, and risk adjustment factors.
• Responsible for the management of numerous managed health care compliance reports and data files, both incoming and outgoing.
• Responsible for the creation and maintenance of business (functional) specifications and technical specifications as well as the creation and maintenance of metadata available to technical personnel and business users.
• Supervision of two data analysts/reporting analysts.
• Create and deliver presentations to various audiences as needed.

Senior Data Analyst/Representative Resume

Objective : Four years of IT- related employment including Data Management: playing key role in writing and execution of test scripts, defect management and providing software life cycle oversight.

Skills : Perl, Teradata, Microsoft Office Suite, Netbeans IDE, MySQL, Eclipse IDE, Project Management, SQL Server, Oracle, Application Developer.

• Responsible for high quality cost variance leadership reporting, Subject Matter Expert for all sales representative hierarchical and channel data, adhoc reporting, enterprise wide product sales reporting.
• Improved data gathering process, for all AT&T sales representative, to enhance reporting accuracy.
• Eliminated none essential manual data collection processes, Standardized data entry procedures, automated data collection and storage.
• Results: Enhanced AT&T Leadership and Channel sales report accuracy, as measured by contrast to actual sales reporting, by 35%.
• Designed Cost Variance Reports for leadership reporting Developed and Managed comprehensive sales records for leadership sales reporting.
• Data Warehousing and ad hoc reporting utilizing: as SQL, Microsoft Access, Teradata, Excel, Java (Netbeans IDE).
• Designed and implemented Consumer Sales reporting tool for service initiatives and employee compensation.
• Assisted technical operators and Business Analyst to resolve problems in running computer program.

Senior Data Analyst/Supervisor Resume

Objective : Over 11+ years of diversified experience in all phases of the Software Development Life Cycle (SDLC). Have worked with requirements elicitation and analysis, database design and development, data analysis, application development, testing, implementation, and support.

Skills : C, Java, C#, Python, SQL, C++, Visual Basic, Visual Studio, Database Management, Venio, Relativity, Recommind, Law Pre-Discovery, Nuix, Exterro, Concordance.

• Successfully interact with clients to develop business needs assessment and project plan documentation.
• Work with clients to supply pre-sale and post-sale analytics reporting to determine return on investment of the claims extend product.
• Teamed with internal IT department and product development to enhance the claims extend product based on customer feedback.
• Defined with client the specific claims data elements to be transferred to McKesson to be processed in the claims extend product.
• Managed the ongoing data transfer for clients focusing on accuracy and data integrity as well as working with the clients to determine customized data elements that would be necessary for reporting.
• Developed client based presentations that reflected return on investment, overall savings, and areas of additional savings opportunities.
• Coordinated client meeting revolving around data transfer and final analytics report output.
• Developed and wrote business needs and requirements documents for customized reports.

Senior Data Analyst/Coordinator Resume

Summary : Over 30 years' experience in developing opportunistic solutions for industry and government; leveraging the synergies of process improvement, enterprise architecture, business analytics, product development, and portfolio management. He has consistently demonstrated his ability to innovate and solve problems to bring about successful transformations and deliver effective outcomes.

• Established and maintained client relationships to create trust and professionalism for approximately 30 clients annually.
• Created data charts and analyses for special projects according to client's specific needs and requests Spearheaded and managed project for designing, maintaining and updating company proprietary software to eliminate antiquated software and keep up with current company needs.
• Prepared OFCCP Audit documents and gathered supporting documentation from clients and their outsourced recruiting vendors.
• Analyzed client workforce and annual personnel activity data to prepare AAP's in accordance to current regulations.
• Determined and assigned census category codes to client job titles to compute external availabilities for protected classes in AAPs.
• Collaborated with Project Manager and Data Processors on discrepancies, client policies and procedures and data errors.
• Provided leadership and direction to keep updated datasets for use in calculation of availability.

Senior Data Analyst/Manager Resume

Summary : Seeking a full-time position in a high quality professional environment where I may assist others while also challenging my own knowledge and skills thus contributing to the success of the organization.

Skills : Microsoft Office, Macros & VBA, Data Analysis, Strong Mathematical Background.

• Increased physician's compensation, streamlined workflows and develops complex financial and business data reports and systems.
• Demonstrate commitment and leadership through quality-based assessments, strategic implementations, and proven ability to manage multiple projects without supervision.
• Serve as designated lead during billing migration projects to add specialty business units into inhouse applications.
• Assist management with new hire training and mentoring of clinical professionals (and office staff) on billing procedures and business applications.
• Monitors charge index system, performs reviews, collects internal/external data for analysis, synchronization, reconciliation, and financial reporting - enhancing performance growth and Revenue Cycle Operations.
• Supplemental functions include practice management and A/R Follow-up.
• Establish and administer workflow policies for tracking and reporting missed charge opportunities with physicians and other stakeholders.

Associate Senior Data Analyst Resume

Objective : Senior Data Analyst is responsible for managing and analyzing data sets, as well as providing support to other departments. The role also includes developing analytical reports and visualizations for the business.

Skills : Microsoft Office Suite for PC and MAC, Statistics Analysis.

• Ensured complete, accurate and timely data was reported from Luke AFB that included 4 aircraft types and 138 total aircraft valued at $3.5 billion.
• Developed policy and procedures and advised and interpreted directives for 13 data analysts.
• Supervised 13 database managers and data analysts who compiled daily, weekly, monthly and annual reports and ad hoc data mining for executive leadership.
• Compiled and validated data from six different aircraft units.
• Provided KPIs, analyzed metrics and generated reports that were used at the highest levels of executive management to make decisions for all units.
• Created Access database and Excel macros that improved data sharing across multiple DB locations.
• Determined new staffing requirements of 700 personnel/9.6K equipment for unit reorganization Assessed end-user requirements and communicated customer's technical needs to development team.
• Effectively served as a communications interface between the two parties.

Senior Data analyst Resume

Headline : 10 plus years of Data analyst experience with over eight years of experience in a variety of industrial environments including insurance, telecom and finance. Attended Sprint plan meetings, Daily standup meetings, and Reviewed user stories in a highly dynamic Agile Environment. Administer operating systems, hardware, and peripheral components, and maintain databases. Perform software installation, upgrades/patches, troubleshooting, and maintenance on UNIX servers.

Skills : Microsoft Office, Visual Basic, SQL, SAS, Stata, Python, R.

• Oversaw tuning and performance monitoring for UNIX/Linux workstations, servers, and peripherals.
• Worked on AWS technologies such as, Redshift.
• Developed OLTP system by designing Logical and eventually Physical Data Model from the Conceptual Data Model and used Erwin tool to develop a Conceptual Model based on business requirements analysis.
• Determined the best approach for designing data structures that support easy data consumption, trends identification, and ability to highlight exceptions through reporting and dashboard tools.
• Involved in architecting the data integration, created the data model for the data warehouse, advised the client on the importance of data governance to consistently maintain the data quality Owned and managed all changes to the data models.
• Created data models, solution designs and data architecture documentation for complex information systems.
• Implemented and documented systems for high-volume production environment.

Senior Data Analyst/Programmer Resume

Objective : Digital marketing professional with 7+ years' experience managing successful digital ecommerce and branding campaigns across multiple channels. Able to work successfully with outside agencies and internal teams to achieve company goals. Detail oriented with excellent planning skills for managing multiple projects with different stakeholders. Perform website diagnostics to improve user experience, managed six figure CPC campaigns utilizing multiple digital channels.

Skills : EPIC, SAS, Six Sigma.

• Deliver actionable insights improving CPC ROAS, website usage, organic search rankings, ecommerce revenue targets, and user experience.
• Design data gathering structure aggregating all relevant metrics and sources providing comprehensive insights and reporting.
• Create, educate, and distribute dynamic dashboards in Google Analytics and Tableau for executives' real-time evaluation.
• Improve customer acquisition through landing page optimizations, and affiliate link building.
• Support suppliers by tracking and reporting product specific web analytics driven from Rite Aid web properties, applications, and mobile websites.
• Create and manage product data feeds for a 25,000 + product catalog containing multiple product attributes destined for multiple CSE platforms, such as EBay, Criteo, Google Shopping, and others.
• Utilize HTML and business knowledge, to optimize product data feeds for higher search rankings, ROAS, cost-per-click, and click through rate.

Asst. Senior Data Analyst Resume

Objective : Twenty years of IT experience includes analysis, design, development, testing, implementation, and maintenance in the Telecommunications, Health Care, Financial, and Consulting industries.

Skills : Enterprise Software, Quality Assurance, Written Communication,.

• Performed statistical analysis of health care data using SAS which were utilized for incentive bonuses, clients' goal setting and performance appraisal.
• Created ad hoc reports and charts to support management decisions in technology expansion.
• Testing Led testing of usability, functionality and data integrity of the client-server system's user interface.
• Developed checklists or standard templates for GUI testing to answer basic questions across all windows within the application.
• Developed systems documentation such as design specifications, user manuals, technical manuals, and description of application operations which was used by developers and technical staff.
• Technical Support Provided software/hardware support to end-users and recommended upgrades, improvements, and integration strategies.
• Trainer Trained new hires and users on existing or new application systems/software.

Senior Data Analyst/Engineer Resume

Objective : Attended Sprint plan meetings, Daily standup meetings, and Reviewed user stories in a highly dynamic Agile Environment. Administer operating systems, hardware, and peripheral components, and maintain databases. Perform software installation, upgrades/patches, troubleshooting, and maintenance on UNIX servers.

Skills : Data analysis, Data warehouse, Data Profili, Data Analysis, healthcare, Data integration, Sql, Oracle, Data Mapping.

• Deliver actionable insights improving usage, organic search rankings, ecommerce revenue targets, and customer satisfaction.
• Design data gathering structure aggregating all relevant metrics and sources so comprehensive insights and reporting are provided.
• Establish, educate, and distribute dynamic dashboards for executives' real-time evaluation.
• Perform independent analysis to inform various presentations and business decisions.
• Improve acquisition, landing page optimizations, and link building for 1,000,000 visit athrough conversion and retention campaigns.
• Support suppliers in tracking and reporting web analytics driven from Rite Aid web properties, applications, and mobile websites.
• Create and manage product data feeds for a 25,000 + product catalog, containing multiple product attributes and destined for multiple CSE platforms, such as EBay, Criteo, Google Shopping, and others.

Senior Data Analyst/Technician Resume

Summary : Highly qualified Senior Data Analyst with experience in the industry. Enjoy creative problem solving and getting exposure on multiple projects, and I would excel in the collaborative environment on which your company prides itself.

Skills : MS Office, Ms Word, Metes and Bounds, Excel.

• Responsible for pagination processes within the Billing and Reporting Team's processing tasks.
• Reports to the Reporting Manager and provides additional data in streamlining and automating tasks/tools for day-to-day duties.
• Prioritize team workloads to meet strict deadlines within pagination processing within our old and new workflow application.
• Ensure that all invoicing gets paginated in a timely manner to bill to all clients and work together with Billing and Sales as needed.
• Processes and uploads data into SAP and rectify any issues or errors with reported data and/or calculations.
• Resolve Billing or client discrepancies as applicable.
• Ensure best practice controls are implements around the Reporting process while preparing and reviewing process documentation is up-to-date.
• Work closely with team members to create and improve implementation processes.

Summary : Process and review over thousands of legal documents yearly while keeping examiners staff ahead of the work-flow providing feedback and maintaining efficiency and accuracy of all legal document being processed and mailed to applicant's stake holders.

Skills : Excel, Pivot Tables, VBA, Access, Macros, Stewardship Reporting, Powerpoint, Tableau.

• Reviewed accuracy of data, monitor performance of system users, provided system users instructions.
• Identified problems, deficiencies and provided assistance in resolving database and report deficiencies.
• Conducted training and inspect system users on installation how to use computer software/equipment.
• Coordinated work plans for maintaining database activity through uploading and downloading of files for over 20,000 personnel with a rating of 95%.
• Assisted task force member with developing and administering a comprehensive training program covering basic and technical job skill.
• Managed the system mobilization and interfacing of an entire military personnel division using the Tactical Army Combat Computer System (TACCS).
• Possess excellent customer service skills to provide technical instructions and guidance on data maintenance procedures.

Table of Contents

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14 Data Analyst Resume Examples for 2024

In this guide, we'll explore proven data analyst resume examples and share clear steps to build a solid profile. Learn to highlight skills like SQL proficiency and data visualization that catch a hiring manager's eye. We include tips on presenting your experience with tools like Python or R, and how to effectively showcase project outcomes. Tailored for new entrants and seasoned professionals in data analysis, this article is your roadmap to a stronger resume.

• 28 Sep 2024 - 1 new section (Showcase leadership and growth) added
• 28 Aug 2024 - 1 new resume template (Data Analytics Consultant) added
• 08 Jul 2024 - 1 new section (Get a score for your resume) added

  Next update scheduled for 26 Oct 2024

Here's what we see in top data analyst resumes.

Show Impact With Numbers : You should show how you've made a difference with numbers. Common metrics include reduced data processing time , increased sales forecasting accuracy , lowered report error rates , and enhanced customer targeting strategies .

Match Skills With Job Description : Include skills you have that are also in the job description. Some strong ones are SQL , Python , data visualization , machine learning , and statistical analysis . Pick the ones you know.

Industry Relevant Tools And Certifications : Good resumes often list important tools and certifications. For example, show certified Tableau expert or mention advanced Excel usage . This shows you have practical skills.

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widget 2: red / but not serious Here's a short quick tip / warning for people to include. If your symptoms get worse or do not improve after 1 day, go to a lower altitude if you can. Try to go around 300 to 1,000 metres lower.

helpful blue / but not serious Here's a short quick tip / warning for people to include. Here's a short quick tip / warning for people to include. Here's a short quick tip / warning for people to include. Here's a short quick tip / warning for people to include. Here's a short quick tip / warning for people to include. Here's a short quick tip / warning for people to include. Here's a short quick tip / warning for people to include.

Data Analyst Resume Sample

Find out how good your resume is.

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Get a score for your resume

Want to know if your resume stands out to employers? Our resume scoring tool gives you instant feedback on your data analysis skills presentation. It checks how well your resume matches what hiring managers in the field look for.

Upload your resume now for a clear, unbiased assessment. You'll get a score and tips to improve your chances of landing interviews for data analyst roles.

Senior Data Analyst Resume Sample

Where to place your education section.

If you're a recent graduate or a current student stepping into a data analyst role, you should place your education in the spotlight. This means placing it before your work experience on your resume. If you've completed further or continuing education such as a master's degree or a bootcamp, highlighting these early on can explain potential gaps in your employment history and showcase your commitment to growth.

For those who've been in the workforce for a while, place your work experience ahead of your education. Your practical skills and hands-on experience in data analysis are what potential employers want to see first.

Junior Data Analyst Resume Sample

Breaking into the data analyst field.

Entering the data analyst field differs from many other industries. You must demonstrate your adeptness in dealing with data. This includes proficiency in statistical analysis software like R or Python, as well as database languages such as SQL. Showcase your relevant experiences in these areas as well as any relevant projects to pique potential employers' interests.

Another important skill is your ability to interpret and present data in a meaningful way. Evidence of strong analytical skills, problem-solving abilities, and communication competencies play a decisive role in demonstrating your potential as a successful data analyst.

Data Engineer Resume Sample

Striking the right length for your resume.

Length is an essential aspect to consider in your resume. Aim to fit your data analyst resume onto one page, especially if you are an entry or mid-level applicant with less than 10 years of experience. A concise and precise resume helps to quickly communicate your qualifications and achievements to potential employers.

Senior-level professionals can extend their resume to two pages. In the case your resume extends beyond one page despite editing, consider opting for a template that optimizes space, or shortening older sections such as education or extracurricular activities.

Data Analyst with Machine Learning specialization Resume Sample

Highlight data visualization skills.

As a hiring manager, I look for your ability to present data in clear, visual formats. To stand out, show how you turn complex data into visuals that anyone can understand.

• List specific visualization tools like Tableau or Power BI that you’ve mastered. Give examples of how you used them to tell a story with data.
• Describe any dashboards or reports you created that led to key business decisions or actions.

Your resume should also reflect how you use visualization to communicate insights. Employers value analysts who not only draw insights from data but also share those insights effectively.

Career Transition to Data Analyst Resume Sample

Understand resume screeners.

When you apply for jobs, your resume often goes through a resume screener called an Applicant Tracking System (ATS). This system looks at your resume to see if it matches the job you want. It is important for you to know how it works so you can make your resume better.

Here are ways to help your resume do well with these systems:

• Use keywords that match the job description. For a data analyst role, include terms like 'data mining', 'SQL', 'Python', 'data visualization', and 'statistical analysis'.
• Make sure your resume is clear and in a format the ATS can read. Use simple headings like 'work experience' and 'education'. Avoid images or charts.

Follow these steps to increase the chance that your resume will be seen by a person.

Lead Business Intelligence Analyst Resume Sample

Capitalizing on industry specifics.

In the data analyst industry, showcasing your technical skills is vital. However, don't forget about your soft skills. Your ability to communicate complex data insights in an understandable way to non-technical team members or stakeholders can make the difference between a good data analyst and a great one.

Furthermore, any evidence of previous work where your data analysis led to successful decisions or changes within a company should be accentuated. This will give potential employers tangible evidence of your ability to create meaningful change with data.

Statistical Data Analyst Resume Sample

Avoid vague language.

When you apply for a job as a data analyst, be clear and specific about your skills and experiences. A common mistake is using vague terms that do not give a clear idea of what you can do. Instead of saying 'knowledge of data analysis tools,' list the specific tools you know how to use, like 'proficient in SQL, Python, and Tableau.' This gives a better understanding of your abilities.

Many resumes also fail to highlight key accomplishments. It is important to show the results of your work. For example, instead of writing 'Responsible for data analysis,' you could say 'Improved sales forecast accuracy by 15% through advanced data analysis.' This tells the reader exactly what you accomplished and how it benefited your previous employer.

Healthcare Data Analyst Specialist Resume Sample

Customize your resume.

You need to show you're right for the job. Focus on what matches the job. Make it easy for hiring managers to see your fit. Tailoring your resume is key to this. It tells us you understand the work and have the skills.

• Show your skills with data. Mention tools you used like SQL or Python . Tell how you used these tools to help your last job.
• If aiming for a senior role, talk about your lead experience. Use numbers like 'led a team of 8 analysts'. Show your work with top managers.
• If you're new to this field, link your old job to the new work. If you worked with numbers, say how. Say you made reports or found ways to cut costs.

Marketing Data Analyst Resume Sample

Showcase your achievements, not just duties.

You need to focus on what you have achieved, not just the tasks you have done. A list of duties won't show how you stand out. Instead, share your successes. These should be specific to being a data analyst.

Here's how to change a responsibility into an accomplishment:

• Before: Responsible for maintaining data accuracy in monthly reporting.
• After: Improved data accuracy by 20% through strategic data cleansing, enhancing the reliability of monthly reporting.
• Before: Managed large datasets for analysis.
• After: Streamlined data analysis by developing a new data management process, cutting down on processing time by 30%.

Financial Data Analyst Resume Sample

Use strong action verbs.

When you create your resume as a data analyst, choosing the right words is key. You need to show that you can do the job well. Use verbs that tell how you handle data and solve problems. This makes your resume stronger and helps employers see your skills.

Start each point in your work experience with a verb that catches the eye. These action verbs should match what a data analyst does every day. Here are some good examples:

• To show you can find and understand data, use analyzed , calculated , assessed , measured , and quantified .
• When talking about how you share your findings, use reported , presented , visualized , articulated , and summarized .
• To show you can make sense of complex information, use interpreted , examined , extrapolated , charted , and decoded .
• If you have improved any processes, highlight this with enhanced , refined , streamlined , optimized , and revised .
• For roles where you led or managed projects, verbs like coordinated , directed , oversaw , supervised , and orchestrated are strong choices.

Want inspiration for other action verbs you can use? Check out synonyms to commonly used action verbs like Coordinated , Increased , Consulting , Build , Performed .

E-commerce Data Analyst Resume Sample

Key skills for data analysis.

As you prepare your resume, focus on the specific skills that show your ability to analyze data effectively. These skills are important to include because they help you pass through applicant tracking systems (ATS) that many companies use to filter resumes.

Here are some top skills you should consider:

• Statistical analysis
• Data mining
• Data modeling
• Database management
• Python or R for data manipulation
• Machine learning
• Data visualization tools like Tableau or Power BI
• Big data platforms such as Hadoop or Apache Spark
• Excel for spreadsheet analysis

You don't need to have all these skills, just those that match the job you want. List your skills in a dedicated section and give examples of how you've used them in your past work in the experience section. This shows employers that you can put your skills into action. Remember, be honest about your skill level to set clear expectations for potential employers.

Senior Data Visualization Specialist Resume Sample

Showcase leadership and growth.

As a data analyst, showing growth in your career is key. You want to make sure you highlight any leadership roles or promotions, as these are strong indicators of your skills and reliability. When crafting your resume, think of times you've taken the lead on projects or have been recognized with a higher position.

• For example, if you led a team to analyze market trends which increased company revenue, mention it. You could write 'Led a team of 4 analysts to develop a new market trend model, resulting in a 10% revenue increase.'
• If you've been promoted, detail the progression. You might say 'Promoted from junior to senior data analyst within 18 months due to strong performance in predictive modeling and team collaboration.'

Even if you're unsure how to show these experiences, you can think about times you've been asked to train new team members or when you've managed a significant part of a project. These are also good signs of leadership and can be included.

• A statement like 'Trained 5 new hires in company-specific data analysis tools and processes' shows leadership.
• Or 'Managed data integration project for new CRM software' reflects both responsibility and the trust your employer placed in you.

Data Analytics Consultant Resume Sample

Quantify your impact.

When you share your past work, numbers can show your impact clearly. They help me see the value you could bring to my team.

Think about how you have used data to make decisions. Did you help save money or time? Maybe you made a process better. Here are ways to show this:

• Include percentages to show changes in efficiency. For example, 'Optimized data queries, leading to a 20% reduction in load times.'
• Use dollar amounts if you helped save or make money, like 'Identified cost-saving opportunities that reduced expenses by $10,000 annually .'

Even if you're unsure of the exact number, estimate. Ask yourself: How much faster did the project finish? How much less did we spend? Look for:

• Time savings , such as 'Automated report generation, saving 10 hours per week.'
• Error reductions in data processing, e.g., 'Improved data accuracy by 15% .'
• Customer satisfaction jumps due to better data analysis, like 'Enhanced customer targeting, increasing satisfaction scores by 25% .'
•   Entry-Level Data Analyst Resume Examples
•   Agile Business Analyst Resume Examples
•   Business Systems Analyst Resume Examples
•   Analyst Resume Examples
•   IT Business Analyst Resume Examples
•   AML Analyst Resume Examples
•   Experienced Data Analyst Resume Examples
•   IT Analyst Resume Examples

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The Official Careers Website of the City of New York

Senior Data Analyst, Bureau of Vital Statistics

• Agency: DEPT OF HEALTH/MENTAL HYGIENE
• Job type: Full-time
• Title Classification: No exam required

Vital Statistics/Vital Records

Job Description

This vacancy has now expired..

The Bureau of Vital Statistics is responsible for registering and certifying all birth, deaths, spontaneous and induced terminations of pregnancy in NYC. The bureau issues, analyzes and reports on 285,000 vital events each year. The bureau is a very large customer service operation, providing death certification services on a 24/7 basis, issuing more than 900,000 certified copies of birth and death records, and fulfilling hundreds of data requests annually. NYC DOHMH has an opening for a Senior Data Analyst. This position will report to the Director of the Statistical Analysis and Reporting Unit in the Bureau of Vital Statistics, Office of Vital Statistics. Staff in this unit work on vital statistics data analyses, data requests, and research projects; they also provide data to DOHMH programs, other government agencies, non-profit organizations, academic researchers, and others for public health and administrative purposes. DUTIES WILL INCLUDE BUT NOT BE LIMITED TO: - Conduct statistical analyses of birth, death, other vital event data, and other registry or survey data, applying standard analytical tools to address the research questions posed. - Serve as Statistical Analysis and Reporting Unit research and analytics lead, providing methodological and analytical assistance and support for individual projects. - Involved in leading planning and implementation of analyses to be conducted in accordance with fiscal year goals and future analytic and research agendas. - In partnership with the Director of the Statistical Analysis and Reporting Unit, answer questions from other staff about advanced statistical methods, including but not limited to learning new methods and educating others in these topics. - Assist with Bureau of Vital Statistics surveillance, programmatic, and research projects, providing consultation, analyses, and/or vital statistics data access for approved users. - Produce Annual Summary of Vital Statistics data tables and figures in collaboration with other data analysts. Collaborate with other analysts, both internal and external, on research projects. - Work independently or collaborate with other internal or external researchers on analyses, reports, and peer-review papers, sharing findings with a wider audience. - Supervise student workers on research projects that will advance analytic priorities of the agency. Represent division, bureau, and office in agency initiatives, as needed. - Other tasks assigned. PREFERRED SKILLS: - A master's degree or doctorate from an accredited college or university with a specialization in an appropriate field of public health, epidemiology, statistics, health economics, or data science. - Academic training in public health, statistics, mathematics, including applied epidemiology. Strong written and verbal communication skills are required. - Extensive experience using SAS and R, and experience using Microsoft Word, Outlook, Excel, Access, and PowerPoint are also required. - Familiarity with languages, such as SQL or Python will be a plus. - Experience of completing analyses using vital statistics data and solid knowledge of statistical and mathematical methods, including experience with advanced analytics. - Self-starter with strong initiative and sound judgment, who is able to work both independently and, in a team, to analyze data and provide written interpretations of both statistical methods and results. - Experience presenting results to expert audiences, via forums like national public health conferences and peer-reviewed manuscripts. - Knowledge and experience with electronic death and birth registration systems, the cause of death coding system within the International Classifications of Diseases (ICD) framework, and experience with large administrative datasets would be ideal. - Experience in demography. Why you should work for us: - Loan Forgiveness: As a prospective employee of the City of New York, you may be eligible for federal/state loan forgiveness and repayment assistance programs that lessen your payments or even fully forgive your full balance. For more information, please visit the U.S. Department of Education’s website (https://studentaid.gov/pslf/) - Benefits: City employees are entitled to unmatched benefits such as: o a premium-free health insurance plan that saves employees over $10K annually, per a 2024 assessment. o additional health, fitness, and financial benefits may be available based on the position’s associated union/benefit fund. o a public sector defined benefit pension plan with steady monthly payments in retirement. o a tax-deferred savings program and o a robust Worksite Wellness Program that offers resources and opportunities to keep you healthy while serving New Yorkers. - Work From Home Policy: Depending on your position, you may be able to work up to two days during the week from home. - Job Security - you could enjoy more job security compared to private sector employment and be able to contribute to making NYC a healthy place to live and work. Established in 1805, the New York City Department of Health and Mental Hygiene (NYC Health Department) is the oldest and largest health department in the U.S., dedicated to protecting and improving the health of NYC. Our mission is to safeguard the health of every resident and cultivate a city where everyone, regardless of age, background, or location, can achieve their optimal health. We provide a wide array of programs and services focused on food and nutrition, anti-tobacco support, chronic disease prevention, HIV/AIDS treatment, family and child health, environmental health, mental health, and social justice initiatives. As the primary population health strategist and policy authority for NYC, with a rich history of public health initiatives and scientific advancements, from addressing the 1822 yellow fever outbreak to the COVID-19 pandemic, we serve as a global leader in public health innovation and expertise. Come join us and help to continue our efforts in making a difference in the lives of all New Yorkers! The NYC Health Department is an inclusive equal opportunity employer committed to providing access and reasonable accommodation to all individuals. To request reasonable accommodation to participate in the job application or interview process, contact Sye-Eun Ahn, Director of the Office of Equal Employment Opportunity, at [email protected] or 347-396-6549.

1. For Assignment Level I (only physical, biological and environmental sciences and public health) A master's degree from an accredited college or university with a specialization in an appropriate field of physical, biological or environmental science or in public health. To be appointed to Assignment Level II and above, candidates must have: 1. A doctorate degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and one year of full-time experience in a responsible supervisory, administrative or research capacity in the appropriate field of specialization; or 2. A master's degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and three years of responsible full-time research experience in the appropriate field of specialization; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least a master's degree in an appropriate field of specialization and at least two years of experience described in "2" above. Two years as a City Research Scientist Level I can be substituted for the experience required in "1" and "2" above. NOTE: Probationary Period Appointments to this position are subject to a minimum probationary period of one year.

The City of New York is an inclusive equal opportunity employer committed to recruiting and retaining a diverse workforce and providing a work environment that is free from discrimination and harassment based upon any legally protected status or protected characteristic, including but not limited to an individual's sex, race, color, ethnicity, national origin, age, religion, disability, sexual orientation, veteran status, gender identity, or pregnancy.

Civil service title

CITY RESEARCH SCIENTIST

Title classification

Non-Competitive-5

Business title

Posted until

• Experience level: Experienced (non-manager)

Number of positions

Work location

42-09 28th Street

• Category: Health

23 Common Senior Data Engineer Interview Questions & Answers

Prepare for your senior data engineer interview with key questions and insights on system architecture, data integrity, scalability, security, and more.

Landing a job as a Senior Data Engineer is like being handed the keys to a kingdom where data reigns supreme. It’s a role that demands not just technical prowess but also the ability to translate complex data into actionable insights that drive business decisions. As you prepare for your interview, it’s essential to arm yourself with the right answers to showcase your expertise and your knack for problem-solving. But don’t worry, we’ve got you covered with a comprehensive guide to the most common interview questions and how to tackle them with confidence and flair.

Think of this as your secret weapon in navigating the interview process. From discussing your experience with data pipelines to demonstrating your proficiency in cloud platforms, we’ll help you articulate your skills in a way that resonates with hiring managers.

What Tech Companies Are Looking for in Senior Data Engineers

When preparing for a senior data engineer interview, it’s essential to understand the unique demands and expectations of this role. Senior data engineers are pivotal in designing, constructing, and maintaining scalable data architectures that support data-driven decision-making across the organization. Their work ensures that data is accessible, reliable, and efficiently processed. While the specifics can vary between companies, there are common qualities and skills that hiring managers typically seek in senior data engineer candidates.

Here are some key attributes that companies look for in senior data engineer employees:

• Technical proficiency: Senior data engineers must possess a deep understanding of data engineering tools and technologies. This includes expertise in programming languages such as Python, Java, or Scala, as well as proficiency with data processing frameworks like Apache Spark or Hadoop. Additionally, they should be well-versed in database systems, both SQL and NoSQL, and have experience with cloud platforms like AWS, Google Cloud, or Azure.
• Data architecture and design skills: A senior data engineer should have a strong grasp of data architecture principles. This includes designing efficient data pipelines, creating data models, and implementing data warehousing solutions. They should be able to architect systems that handle large volumes of data while ensuring data integrity and quality.
• Problem-solving abilities: Data engineering often involves tackling complex challenges related to data integration, transformation, and storage. Companies value candidates who can demonstrate their ability to identify problems, analyze root causes, and develop innovative solutions. This requires a blend of analytical thinking and creativity.
• Collaboration and communication skills: Senior data engineers frequently work with cross-functional teams, including data scientists, analysts, and business stakeholders. Effective communication is crucial for understanding requirements, explaining technical concepts to non-technical team members, and ensuring alignment on project goals. Strong collaboration skills help in fostering a productive team environment.
• Experience with data governance and security: As data privacy and security become increasingly important, senior data engineers should have experience implementing data governance frameworks and security measures. This includes knowledge of data encryption, access controls, and compliance with regulations such as GDPR or CCPA.
• Leadership and mentorship: In a senior role, data engineers are often expected to lead projects and mentor junior team members. Demonstrating leadership skills, such as the ability to guide a team through complex projects and provide constructive feedback, is highly valued.

Depending on the organization, hiring managers might also prioritize:

• Experience with real-time data processing: In industries where real-time data insights are critical, experience with streaming technologies like Apache Kafka or AWS Kinesis can be a significant advantage.

To showcase these skills and qualities effectively, candidates should prepare to discuss their past experiences and accomplishments in detail. Providing concrete examples of how they’ve tackled complex data engineering challenges, led successful projects, or implemented innovative solutions can leave a lasting impression on interviewers.

As you prepare for your interview, it’s important to anticipate the types of questions you might encounter and think critically about your experiences and achievements. This preparation will enable you to articulate your value as a senior data engineer confidently. Let’s delve into some example interview questions and answers to help you get started.

Common Senior Data Engineer Interview Questions

1. what are the differences between data lakes and data warehouses in terms of architecture and use cases.

Understanding the differences between data lakes and data warehouses is essential for choosing the right tool for specific business needs. Data lakes offer flexibility and scalability for storing raw, unstructured data, suitable for exploratory analysis and machine learning. In contrast, data warehouses are optimized for structured data with predefined schemas, ideal for complex queries and business intelligence. This question assesses your ability to navigate architectural choices and align them with organizational goals.

How to Answer: When discussing data lakes and data warehouses, focus on architectural differences and specific business scenarios. Share examples where you’ve implemented or transitioned between these systems, highlighting the outcomes.

Example: “Data lakes and data warehouses serve different purposes and are architecturally distinct. Data lakes are designed to store raw, unstructured data in its native format, making them ideal for data scientists and analysts who need to explore and experiment with diverse datasets for machine learning or advanced analytics. The architecture of a data lake is flat and flexible, allowing for quick ingestion of vast amounts of data without predefined schemas.

In contrast, data warehouses are structured and optimized for query performance and reporting. They use a predefined schema and are best suited for business intelligence and operational reporting, where data is more structured and aggregated. A data warehouse’s architecture is often organized in a star or snowflake schema, which enhances performance for complex queries and ensures data integrity. In my previous role, I implemented both solutions, ensuring that our data lake fed the data warehouse with curated datasets, thereby supporting both exploratory analysis and operational reporting seamlessly.”

2. How do you ensure data quality and integrity in large-scale systems?

Ensuring data quality and integrity in large-scale systems impacts the reliability and accuracy of insights. This question explores your understanding of managing vast data amounts and implementing systems that maintain high data fidelity. It focuses on your approach to preventing data corruption, managing inconsistencies, and establishing robust validation processes, reflecting your capability to foresee potential issues and address them proactively.

How to Answer: Discuss your experience with data validation frameworks, automated testing, and monitoring systems for detecting anomalies. Mention tools and methodologies like ETL processes or machine learning techniques for anomaly detection. Highlight examples where you’ve maintained or improved data quality in complex systems.

Example: “Ensuring data quality and integrity starts with implementing robust data validation protocols at every stage of the data pipeline. I prioritize setting up automated checks that flag anomalies, inconsistencies, or duplications as soon as data is ingested. These checks help to catch any potential issues early on, which is crucial in large-scale systems where bad data can quickly propagate.

Additionally, I advocate for clear data governance policies, ensuring that data definitions and standards are consistent across all teams. This involves regular audits and collaborating closely with data analysts and stakeholders to stay updated on any changes in data requirements or business logic. A recent example involved working with the analytics team to refine our metadata management, which significantly reduced data discrepancies and improved reporting accuracy. Regular communication and iteration are key to maintaining high data integrity.”

3. How would you handle schema evolution in a streaming data pipeline?

Handling schema evolution in a streaming data pipeline involves maintaining data integrity and consistency as structures change over time. This question examines your ability to anticipate and manage change, adapt to evolving data needs, and implement robust yet flexible solutions. It reflects your understanding of the broader data ecosystem and your capability to maintain seamless data flow, impacting operational efficiency and business intelligence.

How to Answer: Explain your approach to managing schema changes, such as using schema registry tools or implementing compatibility measures. Share experiences with schema evolution, highlighting challenges and solutions. Emphasize collaboration with cross-functional teams to ensure alignment.

Example: “First, I’d ensure the pipeline is built with a schema registry that supports versioning. This allows for backward and forward compatibility, which is crucial for handling evolving schemas without interrupting data flow. I would implement a strategy that uses Avro or Protobuf, as these formats efficiently manage schema changes and maintain compatibility.

For example, at my previous company, we faced a situation where new fields needed to be added to a streaming data source, and some existing fields modified. I worked with the data producers to ensure new fields were optional and defaulted to null, preventing disruptions for consumers not yet adapted to the changes. Simultaneously, I maintained comprehensive documentation and clear communication with all stakeholders, ensuring they’re aware of changes and timelines. This approach minimized downtime and kept the data pipeline robust against future schema changes.”

4. Can you discuss your experience with cloud-based data platforms, such as AWS Redshift or Google BigQuery?

Familiarity with cloud-based platforms like AWS Redshift or Google BigQuery is integral to modern data infrastructure due to their scalability and cost-effectiveness. This question delves into your ability to optimize data pipelines, manage storage, and ensure seamless integration across cloud services. Your response can demonstrate proficiency in leveraging cloud technologies to drive data strategies and support organizational objectives.

How to Answer: Detail projects where you’ve used cloud-based platforms, focusing on your role in designing or optimizing data solutions. Discuss challenges faced and resolutions, highlighting efficiencies gained or improvements in data processing capabilities.

Example: “I’ve had extensive experience with cloud-based data platforms, particularly AWS Redshift. In my previous role at a tech company, we migrated our on-prem data warehouse to Redshift to improve scalability and performance. I led the project, collaborating with data architects to design the schema and optimize data models for faster query performance. We implemented best practices for partitioning and indexing, which significantly reduced query times by about 40%.

I also worked closely with our DevOps team to set up automated data pipelines using AWS Glue, which streamlined our ETL processes. This automation reduced manual intervention and errors, allowing our data analysts to access up-to-date information more reliably. Additionally, I’ve dabbled with Google BigQuery in a couple of side projects, appreciating its capacity to handle massive datasets efficiently and its integration with Google’s ecosystem. Both platforms have their strengths, and I’m comfortable leveraging their unique features to meet specific business needs.”

5. How do you ensure scalability in a distributed data processing environment?

Scalability in distributed data processing environments ensures systems can handle increasing data volumes efficiently. This question explores your ability to design systems that meet current demands and are future-proof, reflecting foresight and strategic planning. It’s about demonstrating your capacity to anticipate challenges, optimize resource allocation, and implement solutions that maintain seamless operations as data loads increase.

How to Answer: Discuss your experience with technologies and methodologies for scalability, such as distributed computing frameworks and data partitioning strategies. Highlight projects where you successfully scaled systems, discussing outcomes and lessons learned.

Example: “I prioritize designing systems with modular architectures and leverage technologies like Apache Kafka and Spark for distributed data processing. By decoupling components, I ensure that each part of the system can be independently scaled based on demand. I also incorporate automated monitoring tools like Prometheus to continually assess performance metrics and identify bottlenecks before they become problems.

In a previous role, I worked on a project where we needed to handle rapidly increasing data volumes. We implemented a microservices architecture, which allowed us to independently scale different services based on load. We also utilized cloud-based solutions like AWS Lambda to automatically adjust resources. This approach maintained performance while keeping costs efficient, ensuring that our system could handle both current needs and future growth seamlessly.”

6. What strategies do you employ to secure sensitive data within a database?

Data security is a paramount concern, especially when handling vast amounts of sensitive information. Ensuring data integrity and confidentiality involves implementing a comprehensive strategy that anticipates potential vulnerabilities. This question delves into your understanding of both technical and strategic aspects of data security, revealing your ability to think critically about security protocols and take a proactive approach to safeguarding information.

How to Answer: Focus on strategies for securing sensitive data, such as encryption standards, access controls, and regular audits. Highlight experiences where you mitigated risks or improved security protocols.

Example: “I prioritize a multi-layered approach to secure sensitive data, starting with encryption both at rest and in transit. This ensures that data is protected from unauthorized access, even if someone manages to breach the perimeter. I also implement role-based access control, ensuring that only authorized personnel have access to specific datasets, which minimizes the risk of internal threats.

Regular audits and monitoring are crucial as well. I set up automated alerts to identify any unusual activity or access patterns, which allows me to respond quickly to potential threats. Additionally, I keep the database systems updated with the latest security patches and conduct regular vulnerability assessments to address any potential weaknesses. In a previous role, these strategies collectively reduced our data-related incidents by 30%, showcasing their effectiveness in real-world applications.”

7. What are the trade-offs between batch processing and real-time processing?

Understanding the trade-offs between batch and real-time processing explores your ability to balance latency, resource allocation, and data accuracy. Real-time processing offers immediacy and responsiveness, crucial for instant insights, but demands more computing power. Conversely, batch processing is efficient for handling large volumes without immediacy, offering cost-effectiveness. This question assesses your strategic thinking in choosing the right approach based on project needs and infrastructure capabilities.

How to Answer: Discuss scenarios where you’ve weighed trade-offs between batch and real-time processing. Highlight experiences where you’ve implemented one over the other, explaining your decision-making process considering factors like data velocity and resource constraints.

Example: “Choosing between batch processing and real-time processing often comes down to the specific needs of the business and the nature of the data. Batch processing is great when working with large volumes of data that don’t require immediate insights, like end-of-day financial reports or historical data analysis. It’s cost-effective, as you can schedule it during off-peak hours to optimize resource usage, but the delay in data availability can be a downside when timely decisions are crucial.

On the other hand, real-time processing is essential when you need instant data-driven actions, such as fraud detection in financial transactions or monitoring a live streaming service. The trade-off here is higher resource consumption and increased complexity in handling data streams, which can be mitigated with robust infrastructure and efficient scaling strategies. In a previous role, I worked on a project where we combined both approaches—using real-time processing for immediate alerts and batch processing for in-depth analysis—to balance cost and performance effectively.”

8. Can you describe a time when you implemented a new technology or tool in your data engineering workflow, and what was the outcome?

Adopting new technologies or tools in data engineering is essential for staying ahead in a rapidly evolving field. This question examines your ability to assess the impact of a new tool, manage the transition, and evaluate results. It reflects your capacity to drive innovation, enhance efficiency, and maintain a competitive edge, demonstrating problem-solving skills and adaptability in a dynamic environment.

How to Answer: Focus on a specific instance where you recognized the need for change and took initiative. Detail the steps you took to research and select the technology, manage the implementation process, and overcome challenges. Highlight tangible outcomes like improved performance or cost savings.

Example: “At my previous company, we were struggling with data processing times, which were slowing down our analytics and impacting decision-making. I researched various options and proposed we integrate Apache Spark into our workflow to handle larger datasets more efficiently. I led a small team to pilot this transition, starting with a non-critical segment of our data operations to minimize risk.

We focused first on training, ensuring everyone was comfortable with the new tool, then gradually integrated Spark into our full data pipeline. It was a game-changer; processing times decreased by over 50%, and the team was able to run complex queries in a fraction of the time it used to take. This not only improved productivity but also allowed us to provide more timely insights to our stakeholders, ultimately leading to more informed strategic decisions.”

9. In what scenarios would you choose NoSQL over SQL databases?

Choosing between NoSQL and SQL databases involves understanding data structure, scalability, and application needs. SQL databases offer structured data storage with ACID properties, ideal for complex queries. NoSQL databases provide flexibility and scalability, suitable for unstructured data and rapidly changing requirements. This question probes your ability to make informed decisions based on data integrity, consistency, and performance optimization.

How to Answer: Highlight use cases where NoSQL’s schema-less design and horizontal scaling capabilities surpass SQL’s structured framework. Discuss real-world experiences or projects where a NoSQL database was implemented, addressing potential trade-offs like eventual consistency.

Example: “I typically opt for NoSQL databases when dealing with large volumes of unstructured or semi-structured data that require horizontal scaling and flexible schema design. For instance, in a previous role, we were handling data from millions of IoT devices, each sending different types of data in varied formats. Using a NoSQL database like MongoDB allowed us to efficiently manage this diversity and volume without the rigid schema constraints of SQL databases. It was also crucial for achieving high write performance and availability, given the distributed nature of the data sources. While SQL databases excel in scenarios needing complex queries and transactions, NoSQL shines in agile environments where data structures evolve rapidly.”

10. What are the key considerations when designing a data pipeline for machine learning applications?

Designing a data pipeline for machine learning applications requires balancing data flow, storage, and transformation with model demands. This question explores your approach to ensuring data integrity, scalability, and efficiency, impacting machine learning performance and reliability. It touches on your strategic thinking and ability to foresee challenges, such as data drift, and how you plan to mitigate them to sustain model accuracy.

How to Answer: Emphasize your experience in architecting scalable pipelines for machine learning projects. Discuss techniques for maintaining data quality and optimizing data storage. Highlight collaboration with data scientists to integrate feedback loops into pipeline design.

Example: “Designing a data pipeline for machine learning applications involves several key considerations to ensure efficiency, reliability, and scalability. First, it’s crucial to understand the specific data requirements of the machine learning model. This involves identifying the types of data needed, the volume, and the velocity at which data will be ingested. Ensuring that the data is clean, accurate, and relevant is fundamental, so implementing robust data validation and cleansing processes is essential.

Another critical aspect is scalability and flexibility. The pipeline should be able to handle an increase in data volume over time, so leveraging distributed systems and cloud resources can be beneficial. Additionally, incorporating a modular design allows for easier updates or changes as the machine learning models evolve. Monitoring and logging are also vital to quickly identify and resolve any issues that arise, ensuring minimal downtime and consistent performance. In a previous role, I built a pipeline that incorporated these principles, which significantly improved our model training times and accuracy rates.”

11. Have you integrated data from disparate sources, and if so, what was your approach?

Data integration from disparate sources requires handling varied data formats, structures, and origins into a cohesive system. This question delves into your ability to ensure data integrity, consistency, and accessibility across platforms. It’s about demonstrating how you can orchestrate seamless data integration that supports robust analysis and business intelligence.

How to Answer: Describe a project where you integrated data from multiple sources. Highlight your methodology, tools, and technologies used, and explain your choices. Discuss challenges faced and solutions implemented.

Example: “Absolutely, integrating data from various sources is a crucial part of my role. In a recent project, I was tasked with consolidating data from a legacy system, a cloud-based CRM, and social media platforms for a unified customer analytics dashboard. My first step was to thoroughly understand each data source’s structure and establish a connection to them via APIs or direct database links.

I focused on creating a robust ETL process, where I used Python and SQL to extract and clean the data. I ensured data consistency and quality by employing data validation checks at each stage. I also designed a scalable data pipeline using Apache Kafka to handle real-time data streaming, which allowed us to process incoming data efficiently and keep the dashboard updated. To tie everything together, I leveraged a data lake architecture on AWS S3, which provided us with the flexibility to store and process both structured and unstructured data. This approach not only improved data accessibility and accuracy but also significantly enhanced our team’s ability to make data-driven decisions.”

12. How do you approach capacity planning for data storage and processing needs?

Capacity planning involves forecasting data growth, managing resources efficiently, and aligning technical solutions with organizational goals. This question explores your ability to maintain system performance, optimize costs, and avoid bottlenecks that could disrupt operations. Understanding this question’s importance highlights your strategic thinking and proficiency in managing large-scale data environments.

How to Answer: Emphasize your approach to assessing data infrastructure, predicting future needs, and integrating scalable solutions. Discuss tools and techniques like data modeling and trend analysis. Provide examples of how you’ve met data growth challenges.

Example: “I typically begin by analyzing current data usage patterns and growth trends to establish a baseline. This involves collaborating with the analytics and business teams to understand both current and projected data needs. I then model different scenarios to anticipate future requirements, considering factors like new projects, partnerships, or changes in data compliance regulations that might impact storage needs.

With this information, I evaluate our existing infrastructure to identify any potential bottlenecks or areas for improvement, balancing cost with performance and scalability. I also stay in tune with the latest technologies and cloud-based solutions, which allows for flexibility in scaling up or down based on real-time needs. By regularly reviewing and updating the capacity plan, I ensure that we can handle increased data volumes seamlessly, while maintaining optimal performance and cost efficiency.”

13. Which data serialization formats have you used, and why did you choose them?

Selecting specific data serialization formats reflects your ability to optimize data storage, transmission, and processing efficiency. Different formats, like JSON, Avro, or Parquet, have unique advantages related to speed, compression, and compatibility. This question highlights your ability to make informed decisions that impact the scalability and performance of data systems.

How to Answer: Articulate your thought process in selecting data serialization formats, discussing scenarios and requirements that influenced your choice. Highlight benefits and limitations of each format and provide examples of positive impacts on data processing tasks.

Example: “I’ve worked extensively with JSON, Avro, and Parquet, each chosen based on specific project needs. JSON is my go-to for web applications because its human-readable format makes it easy to debug and integrate with various APIs, especially during the initial development phase when flexibility is crucial.

For projects that involve schema evolution and require efficient serialization with a focus on backward and forward compatibility, I lean towards Avro. It’s particularly useful in data streaming scenarios where consistent schema management is vital. For data warehousing and analytics, Parquet is my preferred choice due to its columnar storage format, which significantly improves query performance and reduces storage costs. For instance, in a recent analytics project, using Parquet reduced our storage needs by 30% and accelerated query times by nearly 40%, which was critical for our data pipeline efficiency.”

14. How do you stay updated on emerging trends and technologies in data engineering?

Staying current with emerging trends and technologies is essential for maintaining a competitive edge and ensuring data solutions’ efficacy. This question examines your commitment to continuous learning and proactive professional development. It reflects how you integrate new knowledge into your work, impacting a company’s ability to innovate and adapt to market changes.

How to Answer: Discuss methods and resources you use to stay informed, such as industry conferences or online courses. Highlight recent technologies or trends you’ve integrated into your work and the results or improvements achieved.

Example: “I make it a priority by dedicating time each week to explore a mix of resources. I subscribe to a few key industry newsletters and follow influential data engineering leaders on platforms like LinkedIn and Twitter. I’ve found that engaging with online communities and forums, such as Reddit’s data engineering subreddit, provides real-time insights and practical advice from peers facing similar challenges.

I also attend webinars and conferences—though virtually these days—to hear firsthand about the latest tools and techniques. Whenever possible, I enroll in online courses to deepen my understanding of specific technologies that catch my interest. Recently, I completed a course on streaming data pipelines, which I’ve started integrating into my current projects. This multifaceted approach keeps me informed and allows me to apply cutting-edge solutions to real-world problems effectively.”

15. What is the purpose of data partitioning, and how does it impact query performance?

Data partitioning enhances query performance by dividing large datasets into manageable segments, allowing efficient data retrieval. This question reflects your ability to optimize data processing and storage, crucial for handling large-scale environments. It assesses your strategic decisions on partitioning schemes that align with query patterns and business needs, ensuring scalable and performant data systems.

How to Answer: Focus on understanding how data partitioning can reduce I/O operations and improve query performance. Discuss partitioning strategies like range or hash partitioning and how you’ve applied them in past projects.

Example: “Data partitioning is crucial for optimizing query performance, especially when working with large datasets. By dividing a dataset into smaller, more manageable segments based on specific keys such as date or ID, you enable parallel processing and reduce the amount of data scanned for a query. This can significantly speed up query response times.

In my previous role, we implemented partitioning on a massive customer transaction dataset. We chose to partition by transaction date, which allowed us to quickly retrieve and process only the relevant data for time-specific queries, rather than scanning the entire dataset. This not only improved performance but also reduced resource consumption and costs. As a result, the team was able to run complex analytical queries much more efficiently, which directly contributed to faster decision-making processes within the company.”

16. How do you handle data versioning in your projects?

Data versioning is crucial for managing complex data pipelines and ensuring reproducibility and traceability. This question delves into your technical proficiency and strategic thinking, requiring you to balance consistency and accuracy with flexibility for evolving datasets. Effective data versioning impacts the reliability and credibility of data-driven decisions.

How to Answer: Articulate your approach to data versioning, discussing tools and methodologies like Git or Delta Lake. Highlight challenges faced and solutions implemented to ensure data integrity.

Example: “I ensure robust data versioning by incorporating a combination of tools and practices that maintain data integrity and reproducibility. Version control systems like Git are essential for tracking changes in code and configuration files, but for datasets, I leverage data versioning tools such as DVC or Delta Lake. These tools allow me to maintain a clear history of data changes and ensure that each version of the data is tied to specific model versions or experiments.

For example, in a previous project, we had multiple teams working on the same dataset, and it was crucial that everyone was aligned on which version they were using. By implementing DVC, we were able to track changes and ensure that any data processing or model training could be reproduced exactly. This approach not only facilitated collaboration but also significantly reduced errors related to data inconsistencies. Regular audits and documentation further support this process, ensuring that every stakeholder has access to the correct data versions and understands their lineage and transformations.”

17. What tools or practices do you recommend for monitoring data pipeline health?

Ensuring the sustained performance and reliability of data pipelines is essential for supporting decision-making and operational efficiency. This question explores your expertise in maintaining data flow integrity and efficiency, revealing your familiarity with industry-standard tools and practices. It assesses your strategic approach to maintaining robust data systems, impacting organizational agility and responsiveness.

How to Answer: Emphasize your experience with tools and practices for monitoring pipeline performance. Discuss how you’ve implemented solutions to address potential bottlenecks or failures, ensuring data accuracy and availability.

Example: “I recommend employing a combination of automated monitoring tools and manual checks to ensure data pipeline health. Tools like Apache Airflow and Apache NiFi are excellent for orchestrating and monitoring workflows, as they provide built-in alerting and logging features. For real-time monitoring, I often suggest using Prometheus with Grafana, as they offer robust metrics collection and visualization capabilities.

Additionally, implementing practices such as data quality checks and anomaly detection can preemptively catch issues. I like to set up automated tests that validate the data at each stage of the pipeline, ensuring accuracy and consistency. Building in redundancy and having a clear incident response plan is also crucial. In my last role, setting these elements up reduced our downtime significantly and allowed us to catch potential issues before they impacted end users.”

18. How would you propose minimizing latency in data processing workflows?

Latency in data processing can impact performance and efficiency. This question examines your ability to identify bottlenecks and implement solutions that enhance data throughput and system responsiveness. It reflects your technical prowess and strategic thinking, essential for optimizing data infrastructure in a fast-paced environment where timely data access drives decision-making.

How to Answer: Discuss tools and techniques for reducing latency, such as parallel processing and caching strategies. Highlight technologies like Apache Kafka or Spark and how you’ve configured them to improve data flow.

Example: “For minimizing latency, I’d start by ensuring that we’re leveraging distributed processing frameworks like Apache Spark, which can handle large datasets efficiently in parallel. I’d also evaluate our existing data architecture to identify any bottlenecks. For example, if we’re using traditional ETL processes, I’d propose transitioning to a more real-time approach with stream processing using tools like Kafka or Flink to reduce wait times.

Another key area is optimizing our data storage and retrieval strategies. Implementing partitioning and indexing in our data warehouses can significantly speed up access times. I’d also look into caching frequently accessed data to cut down on redundant processing. In a previous role, I led a project where we restructured our data pipelines and reduced latency by 40%, which greatly improved the performance of our analytics dashboards. This involved a mix of architectural changes and tuning the configurations of our processing tools to better suit our data patterns.”

19. What are the benefits and drawbacks of using containerization for data workloads?

Containerization offers flexibility and efficiency in managing data workloads. Understanding its nuances impacts scalability, resource allocation, and deployment consistency. This question delves into your ability to weigh benefits like seamless integration against drawbacks like orchestration complexity, making informed decisions that align with organizational goals.

How to Answer: Focus on your experience with containerization in projects and your thought process in evaluating trade-offs. Highlight instances where you implemented or decided against using containers, explaining your choices.

Example: “Containerization offers a flexible and scalable environment for data workloads, which is a significant advantage. By packaging applications and their dependencies together, containers make it easier to deploy across different environments—whether it’s on-premises, in the cloud, or a hybrid setup. This ensures consistency and reduces the “it works on my machine” problem. Additionally, containers can improve resource utilization and efficiency, as they allow multiple workloads to run on the same infrastructure without interfering with each other.

However, there are drawbacks to consider. Containers can introduce complexity in orchestration and management, particularly when scaling applications across clusters. You’ll need tools like Kubernetes, which come with their own learning curve and maintenance overhead. Also, while containers are lightweight compared to virtual machines, they still add an abstraction layer that can impact performance for highly demanding data workloads. It’s crucial to evaluate the specific needs of your data pipeline to determine if the benefits of containerization outweigh the potential challenges.”

20. Can you demonstrate your understanding of distributed computing frameworks besides Hadoop and Spark?

Familiarity with distributed computing tools beyond Hadoop and Spark reflects your ability to innovate and optimize data processing workflows. This question examines your understanding of alternative frameworks and how they can be strategically applied to solve complex data challenges. It assesses your capacity to adapt to evolving technologies and select tools that align with project goals.

How to Answer: Highlight your experience with lesser-known or emerging frameworks, discussing scenarios where you’ve applied them successfully. Provide examples of their impact on project outcomes, like improved processing speed or reduced costs.

Example: “Absolutely, while Hadoop and Spark are the heavyweights, I’ve also worked with Apache Flink and Dask, which offer some unique advantages. Apache Flink, for instance, excels in real-time data processing and streaming analytics, providing low latency and high throughput. It’s particularly useful for applications requiring complex event processing and stateful computations. I’ve utilized Flink in a project where real-time processing was crucial for a financial services company. We needed to detect fraudulent transactions as they occurred, and Flink’s event-driven architecture allowed us to implement a solution that was both efficient and scalable.

On the other hand, Dask is a great tool for parallel computing in Python, which I’ve used in data science projects that required heavy computation without the overhead of deploying a Hadoop cluster. It integrates seamlessly with existing Python libraries, making it ideal for scaling data processing tasks on a single machine or across a cluster. In a previous role, I leveraged Dask to accelerate data preprocessing tasks for machine learning pipelines, substantially reducing processing time while maintaining flexibility and ease of use.”

21. What strategies do you use to optimize query performance in large datasets?

Handling large datasets involves optimizing complex queries, affecting system performance and efficiency. This question delves into your technical proficiency and experience in addressing real-world data challenges, emphasizing problem-solving skills and understanding of database systems. Your approach to query optimization reveals familiarity with tools and techniques that ensure smooth and effective data systems.

How to Answer: Provide examples and techniques for enhancing query performance, such as indexing strategies or query refactoring. Discuss tools or technologies used, like SQL optimizers, and how they were applied in past projects.

Example: “I start by examining the query execution plans to identify bottlenecks and then focus on indexing strategies. Proper indexing can significantly reduce query times, so I assess the existing indexes and optimize them based on the query patterns. Normalization and denormalization are also tools I utilize depending on the use case; sometimes breaking down data reduces redundancy, while at other times, aggregating data speeds up read operations.

Partitioning large tables is another strategy I often employ, especially when dealing with time-series data. This minimizes the amount of data scanned in each query. Additionally, I make use of caching mechanisms for frequent queries, ensuring that the system isn’t recalculating results unnecessarily. In a previous project, these combined strategies reduced our query times by over 40%, allowing the team to make data-driven decisions more swiftly.”

22. Can you discuss a project where you implemented machine learning models into a data pipeline?

Integrating machine learning models into data pipelines enhances a company’s ability to derive insights and make data-driven decisions. This question showcases your technical proficiency, project management skills, and ability to translate complex algorithms into practical solutions. It highlights your role in bridging the gap between raw data and actionable intelligence, contributing to strategic goals.

How to Answer: Focus on a project where you integrated machine learning models into a data pipeline. Detail challenges faced, strategies employed, and the impact on the business. Highlight collaboration with data scientists and stakeholders.

Example: “Certainly. I led a project where we integrated predictive analytics into our data pipeline to forecast customer churn for an e-commerce platform. I collaborated closely with our data science team to understand the model requirements and ensure our data architecture could seamlessly support these new components.

We decided to use a blend of real-time and batch processing to handle both immediate insights and historical analysis. I built out the ETL processes to clean and transform the data, focusing on optimizing the pipeline for speed and scalability. Implemented Apache Kafka for real-time data ingestion and Spark for processing, which allowed the machine learning models to receive clean, structured data efficiently. After deploying the model, I set up monitoring and logging to ensure it was performing as expected and iterated on the pipeline based on feedback from the data scientists. The project resulted in a significant reduction in churn prediction time, enabling the business to proactively engage with at-risk customers.”

23. How do you analyze the implications of GDPR on data storage and processing?

Understanding GDPR’s implications affects how data is collected, stored, and processed, impacting system architecture and data governance. This question delves into your ability to align technical solutions with legal requirements, showcasing strategic thinking and foresight in managing data responsibly. It assesses your capability to navigate legal frameworks, ensuring compliance and upholding ethical standards.

How to Answer: Emphasize your approach to integrating GDPR principles into data engineering processes. Discuss methods or tools for compliance, like data anonymization or access controls. Highlight collaboration with legal and compliance teams.

Example: “I start by conducting a thorough audit of the data we currently store, focusing on identifying and cataloging personal data as defined by GDPR. Then I assess data flow processes to ensure compliance in both storage and transfer. I collaborate closely with legal and compliance teams to interpret requirements and translate them into technical specifications. This might involve anonymizing data where possible and ensuring we have consent trails for data collection.

In a past role, we faced a similar situation when GDPR first rolled out. I led a cross-functional team to implement changes, such as data minimization and encryption, and we established an ongoing audit process to routinely check compliance. This not only ensured we met regulatory requirements but also increased our users’ trust in how we handled their data.”

23 Common SQL Data Analyst Interview Questions & Answers

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Google | Austin, TX, USA ; Cambridge, MA, USA ; +6 more ; +5 more

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 12 years of experience in a sales role in the enterprise software, cloud, or AI space.
• Experience identifying CCaaS use cases to solve customer challenges, selling Customer Experience, or AI technology to clients.
• Experience in, or supporting the healthcare life sciences or financial services industry.
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Manufacturing Test Development Engineer, Google Cloud

Google | Taipei, Taiwan

• 8 years of experience developing with Python, Java or C++.
• Experience in managing suppliers and partners in implementing design requirements.

Software Engineering Manager II, AI/ML GenAI, Google Ads

Google | Mountain View, CA, USA

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.
• 5 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Director, Workplace and User Experience

Google | Sunnyvale, CA, USA ; Atlanta, GA, USA ; +3 more ; +2 more

• 15 years of experience in workplace strategy, design, or a related field.
• 5 years of experience in people management.

Cloud Consultant I, Infrastructure, Professional Services, Google Cloud (English, Spanish)

Google | Buenos Aires, Argentina

• Bachelor's degree in Computer Science or equivalent practical experience.
• 4 years of experience in project management and technical solution delivery.
• Experience in networking, compute infrastructure (e.g. servers, databases, firewalls, load balancers) and architecting, developing, or maintaining cloud solutions in virtualized environments.
• Experience in one or more of the following: Networking, DevOps, Security, Compute, Storage, Hadoop, Kubernetes, or SRE.
• Ability to communicate in English and Spanish fluently to engage with local stakeholders.

Senior UX Researcher, gTech Users and Products

Google | Boulder, CO, USA ; Atlanta, GA, USA

• 5 years of experience in an applied research setting, or similar.
• Experience with research design utilizing various methods (e.g., usability studies, contextual inquiry, surveys, etc.).

Product Support Manager, gTech Users and Products Editors

Google | New York, NY, USA

• 5 years of experience in a project management, analytical role, or similar.

Camera Software Engineer, Project Starline

Google | Mountain View, CA, USA ; Seattle, WA, USA

• 2 years of experience with software development in one or more programming languages (e.g., C++) or 1 year of experience with an advanced degree.
• 2 years of experience with data structures or algorithms.
• 2 years of experience working with embedded operating systems.
• 2 years of experience with cameras or Android development.

Customer Engineer III, AI/ML, Central, Google Cloud

Google | Addison, TX, USA

• 8 years of experience as a sales engineer or technical consultant in a cloud computing environment or in a customer-facing role.
• Experience in virtualization or cloud native architectures in a support role.
• Experience with big data, machine learning, and numerical programming frameworks (e.g., TensorFlow, Python, MATLAB).
• Experience using an AI platform to build, deploy, and manage machine learning models.

Software Engineer III, Full Stack, YouTube

YouTube | San Bruno, CA, USA ; Mountain View, CA, USA

• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
• 2 years of experience with data structures or algorithms in either an academic or industry setting.
• 2 years of experience with full stack development, across back-end such as Java, Python, GO, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.

New Business Account Strategist, Onboarding, Google Customer Solutions

Google | San Francisco, CA, USA

• 2 years of experience in media account management or the advertising industry.
• Experience in a customer-facing role working with digital advertising products (e.g., Google Ads, Google Shopping, Google Analytics, etc.).

Senior UX Writer, Travel Ads

Google | Seattle, WA, USA ; Irvine, CA, USA ; +2 more ; +1 more

• 6 years of experience in writing, editorial, marketing, UX writing, content design, or related, as well as leading content strategy projects.
• Experience on UX-focused product writing and shaping content for multi-disciplinary projects.
• Include a portfolio , website, or any other relevant link to your work in your resume (providing a viewable link and/or access instructions).

Program Manager, Intake and Mobilization

Google | Boulder, CO, USA

• 3 years of experience in program or project management.
• Experience with analyzing data, database query (e.g. SQL), or creating dashboards/reports

Senior Account Executive, Mid-Market Sales, Google Customer Solutions

• 8 years of experience in digital marketing, digital media, or advertising sales.
• Experience influencing or selling to C-level stakeholders.

Administrative Business Partner, Cloud AppEco

Google | Hyderabad, Telangana, India ; Bangalore, Karnataka, India

• 2 years of experience experience in a high-tech or international environment working on core administrative tasks (e.g., travel management, expense reports, calendar management, facilities coordination, etc).

International Tax Counsel

Google | Atlanta, GA, USA ; Chicago, IL, USA ; +2 more ; +1 more

• Bachelor's degree in Accounting or Finance, or equivalent practical experience.
• 10 years of experience in tax.
• 7 years of experience in international tax with a law firm, accounting firm, or in-house tax department.

Google Experience Operations Manager

Google | Bengaluru, Karnataka, India

• 10 years of experience in HR, operations, process improvement, or relevant field.

Scaled Delivery Manager, gTech Ads Solutions

Google | Taguig, Metro Manila, Philippines

• 5 years of experience building relationships with stakeholders or clients.
• 3 years of experience in a customer or client-facing role in Digital Marketing, Operations Management or Consulting.
• 3 years of experience identifying issues in processes and creating solutions, and working with cross-functional teams.

Generative AI Evaluation Clinical Scientist

Google | Mountain View, CA, USA ; Seattle, WA, USA ; +2 more ; +1 more

• Medical degree (e.g., MD, MBBS, or equivalent degree) or a PhD in Health Informatics, Psychology, Biomedical Engineering, Epidemiology or relevant field with formal research training.
• 3 years of experience applying qualitative and quantitative research methods relevant to health AI model validation.
• Experience implementing analysis with tools relevant to AI evaluation.

Business Intelligence Developer I, Google Cloud

Google | Mexico City, CDMX, Mexico

• 4 years of experience in data modeling, developing data sets, or creating data visualizations.
• Experience writing SQL queries.
• Experience using Business Intelligence (BI) tools like Looker, Tableau, or Power BI to create visualizations and dashboards.

A Singapore Government Agency Website 

Official website links end with .gov.sg

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Senior/ Data Analyst, Vigilance & Compliance Branch (VCB)

Health Sciences Authority

What the role is

What you will be working on

• Develop statistical analysis plans and perform analyses for clinical database studies related to drug safety.
• Conduct data quality assessments and ensure accuracy and fit-for-purpose data usage.
• Participate in data analytic projects to support post-marketing surveillance activities of health products.
• Contribute towards the development of an active safety monitoring programme for medicines including creating study protocols and writing SOPs
• Contribute, as an main author / co-author for journal publications, conference abstracts and posters.
• Supervise student interns as required
• Perform other related duties as assigned

What we are looking for

• Strong background and experience in pharmacy, epidemiology with additional training in related scientific disciplines, e.g. biostatistics, health informatics, or equivalent technical fields with 2-3 years of experience.
• Prior experience in hospital pharmacy practice, medication safety, pharmacovigilance or experience in causal inference methods will be an advantage.
• Experience in analysing electronic health records and assessing data quality and fit-for-purpose.
• Proficient in at least one statistical programming language (e.g. R, Stata or Python) and SQL.
• Peer-reviewed journal publications in topics related to drug safety 
• Good interpersonal, communication, presentation and writing skills

About Health Sciences Authority

The Health Sciences Authority (HSA) applies medical, pharmaceutical and scientific expertise through its three professional groups, Health Products Regulation, Blood Services and Applied Sciences, to protect and advance national health and safety. HSA is a multidisciplinary authority. It serves as the national regulator for health products, ensuring they are wisely regulated to meet standards of safety, quality and efficacy. As the national blood service, it is responsible for providing a safe and adequate blood supply. It also applies specialised scientific, forensic, investigative and analytical capabilities in serving the administration of justice. For more details, visit http://www.hsa.gov.sg/. For more updates on public health and safety matters, follow us on Twitter at www.twitter.com/HSAsg and LinkedIn at https://sg.linkedin.com/company/health-sciences-authority.

Senior Financial Analyst (Data Center Finance)

CoreWeave is the AI Hyperscaler™, delivering a cloud platform of cutting edge services powering the next wave of AI. The company’s technology provides enterprises and leading AI labs with the most performant, efficient and resilient solutions for accelerated computing. Since 2017, CoreWeave has operated a growing footprint of data centers covering every region of the US and across Europe. CoreWeave was ranked as one of the TIME100 most influential companies of 2024.

As the leader in the industry, we thrive in an environment where adaptability and resilience are key. Our culture offers career-defining opportunities for those who excel amid change and challenge. If you’re someone who thrives in a dynamic environment, enjoys solving complex problems, and is eager to make a significant impact, CoreWeave is the place for you. Join us, and be part of a team solving some of the most exciting challenges in the industry. 

CoreWeave powers the creation and delivery of the intelligence that drives innovation. To learn more about our values, please visit our  careers website .

CoreWeave is a specialized cloud provider, delivering a massive scale of GPU compute resources on top of the industry's fastest and most flexible infrastructure. CoreWeave builds cloud solutions for compute intensive use cases — VFX and rendering, machine learning and AI, batch processing, and Pixel Streaming — that are up to 35 times faster and 80% less expensive than the large, generalized public clouds. Learn more at www.coreweave.com .

About the role:

We are seeking a high-performing, self-driven Senior Financial Analyst to join our strategic finance team. The Senior Financial Analyst will support the Director of DC finance, Head of FP&A, and SVP of Data Centers to support data center deal economics, long-term capacity planning, and strategic analysis.  This person will work cross-functionally with a variety of stakeholders at all levels of Coreweave and have frequent opportunities to interact with and support key executive level decision makers. Optimally, this person will have previous experience with data center infrastructure, co-locations providers and exceptional abilities in complex financial modeling, and a strong understanding of economic analysis.

Key Responsibilities:

• Lead and Support the financial analysis for all data center deals including financing and deal structures.
• Independently build, rigorously maintain, and articulately defend analyses on a project-by-project basis 
• Own infrastructure reporting and forecasts, including complex multiregional capital expenditure models and unit economics analysis across a large fleet of computing assets
• Coordinate closely with business development and Operations teams to track, report, and forecast infrastructure-related KPIs
• Generate monthly, quarterly, and annual reports on financial results, budget variance analysis, scenario analysis, stress tests, and KPI results, communicating the analyses to key stakeholders like executive leadership, board members, and other CoreWeave departments
• Collaborate with CFO and CSO to assist with highly impactful, complex, and visible projects, including large scale capital markets and fundraising initiatives 
• Support Accounting team on improvement of accounting and reporting processes
• Assist in evaluating and executing on M&A and direct investment opportunities, including financial analyses, execution, due diligence, and integration 

Requirements:

• A bachelor’s degree in finance, accounting, applied mathematics, economics, engineering, or other business/technical major is required, or an equivalent combination of education and experience
• 3-5+ year(s) of experience in a FP&A, corporate development, investment banking, private equity, or similar roles
• Exceptional  financial modeling and analytical skills, with a demonstrated track record of executing complicated financial analyses 
• Ability to thrive in an extremely fast-paced, ambiguous environment
• Excellent verbal and written communication skills, with a preference for candidates that have demonstrably interacted with management or other executive-level stakeholders
• High level of self-sufficiency with proven success at self-teaching and a high intellectual motor 
• Strong analytical, quantitative, and problem-solving skills
• Exceptional attention to detail, organizational skills, and ability to manage multiple competing priorities simultaneously
• Advanced proficiency with Microsoft Office Suite, particularly Excel and PowerPoint
• Experience with NetSuite, Mosaic.tech, Salesforce, SQL or Power BI experience a plus
• Must be eligible to work in the United States; no H1-B visa sponsorship available

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $115,000-$135,000. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.

What We Offer

The range we’ve posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location.

In addition to a competitive salary, we offer a variety of benefits to support your needs, including:

• Medical, dental, and vision insurance - 100% paid for by CoreWeave
• Company-paid Life Insurance 
• Voluntary supplemental life insurance 
• Short and long-term disability insurance 
• Flexible Spending Account
• Tuition Reimbursement 
• Mental Wellness Benefits through Spring Health 
• Family-Forming support provided by Carrot
• Paid Parental Leave 
• Flexible, full-service childcare support with Kinside
• 401(k) with a generous employer match
• Flexible PTO
• Catered lunch each day in our office and data center locations
• A casual work environment
• A work culture focused on innovative disruption

Our Workplace

At CoreWeave, we are committed to operating as a hybrid workplace, offering employees flexibility in how they structure their time between in-office and remote work. We recognize the significance of fostering connections, collaboration, and creativity within our office culture and its positive impact on our business. Our philosophy operating as a hybrid workplace underscores our dedication to enabling employees to tailor work-life balance to their individual preferences.

For those who do not live within 30 miles of one of our offices, we are open to considering remote work for candidates whose skills and experience strongly align with the role. While we prioritize a hybrid work environment for most roles, we understand the importance of flexibility and are open to remote work for specific positions and specialized skill sets. Onboarding is essential to your success. New employees not based out of an office will be invited to attend onboarding training at one of our hubs within their first month of employment. We continue to foster a collaborative environment by bringing teams together quarterly.

California Consumer Privacy Act - California applicants only

CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information.

As part of this commitment and consistent with the Americans with Disabilities Act (ADA) , CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: [email protected].

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As set forth in CoreWeave’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

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