Sr Data Analyst Data Analytics

Job Summary

The Senior Data Analyst is responsible for the accurate and timely execution of analytic and statistical work supporting client products and revenue-generating initiatives. This role applies established statistical methods, develops analytic code, and delivers high-quality, well-documented outputs for assigned analytic workstreams. Senior Data Analysts operate as experienced individual contributors who independently implement analytic projects, support client and internal requests, and collaborate with multi-functional partners. This position may have assigned clients for which the Senior Analyst is accountable for statistical deliverables. The role follows established processes and standards, exercises sound analytic judgment within defined scope, and contributes hands-on expertise to incremental improvements in analytic workflows, systems, and tools.

Responsibilities

• Accountable for the accurate, on-time delivery of statistical deliverables for assigned projects, including proactively managing workload and standard request queues within the Data Analytics team.
• Implement analytic and research projects by confirming objectives, translating client or business needs into defined analytic approaches, applying appropriate methodologies, and delivering final analytic outputs.
• Independently build, validate, and present statistically sound models using standard tools, programs, and methodologies, making informed decisions under ambiguity, and exercising judgment to identify when creative or non-standard approaches are required and when escalation is appropriate.
• Perform original research and contribute to research requests; maintain clear and comprehensive analytic documentation across the project lifecycle; and develop client-ready materials that clearly communicate findings, implications, and data-driven recommendations, exercising judgment and standing behind analytic conclusions while considering business, client, and operational tradeoffs.
• Consult with Sales personnel and external clients by supporting client meetings and conference calls, explaining statistical concepts, and serving as a trusted analytic advisor.
• Work cross functionally with internal teams, including Client Services, Data Acquisition & Performance, Modeling/Stats, T&D, Production, and Product partners, to troubleshoot data, modeling, and process issues, build effective peer level relationships, clearly explain root causes and recommended solutions, and proactively surface risks or issues before they impact delivery.
• Support the development of peers through informal mentoring, knowledge sharing, and collaboration, contributing to team learning and continuous improvement.
• Write new Python (and PySpark, where applicable) code, enhance and maintain existing codebases, apply relevant industry techniques and trends, and provide input on improvements to modeling methodologies and analytic workflows.
• Ensure compliance with applicable privacy, data governance, and AI guidelines across all assigned analytic work, including the responsible use of AI-enabled tools to improve efficiency and accuracy where appropriate.

Qualifications

• 5+ years os experience.
• Bachelors in statistical, quantitative, or related field.
• Advanced degree preferred; minimum 3 years experience in a statistical field, including experience performing data analysis or modeling with large transactional databases, conducting original research, and working directly with external clients in a business environment.
• Experience working with external clients in a business environment and familiarity with Epsilon data products, processes, and direct marketing concepts preferred.
• Advanced knowledge of statistical methods and principles, including regression, clustering, factor analysis, ANOVA, sampling, inference, transformations, validation, and model evaluation techniques.
• Demonstrated ability to conduct analytic projects and research through all stages, including problem formulation, metric definition, methodology selection, execution, evaluation, and final reporting.
• Proficiency in analytic programming and tools, including Python (and PySpark where applicable) and SQL, with the ability to independently perform analyses, understand, improve, and maintain existing codebases, review peer analytic work for quality and correctness, and contribute to informal knowledge sharing and skill development; proficiency in Excel and PowerPoint to support analysis, reporting, and presentations.
• Experience using LLM- and AI-enabled tools to support analytic review, accelerate team workflows, and enhance documentation and knowledge sharing, while ensuring alignment to governance and responsible-use standards.
• Demonstrable ability to manage multiple projects concurrently, prioritize effectively, and work independently with minimal oversight while maintaining good attention to detail and analytic rigor.
• Excellent analytical, troubleshooting, communication, and consulting skills, including the ability to communicate complex analytic concepts clearly to technical and non-technical audiences, collaborate effectively with multi-functional teams, support informal knowledge sharing, and travel occasionally to meet client or business needs.

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