Lead Data Analyst

See how Epsilon powers connected marketing by unlocking the full potential of data and identity.

See how Epsilon powers connected marketing by unlocking the full potential of data and identity.

The Lead Statistician is responsible for the accurate and timely execution of analytic and statistical work supporting Epsilon clients, products, and revenue-generating initiatives. This role applies advanced statistical methods, develops analytic code, and delivers high-quality, well-documented outputs for assigned analytic work streams.

Lead Statisticians operate as senior-level individual contributors who independently lead and execute complex analytic projects, support client and internal requests, collaborate with cross-functional partners, and provide guidance and direction to other team members in support of statistical deliverables. This position may have assigned clients for which the Lead Statistician is accountable for statistical deliverables. The role applies sound analytical judgment and follows established processes and standards across a broader scope of work, serves as a subject matter resource within the team, and contributes hands-on expertise to drive incremental improvements in analytic workflows, systems, and tools.

• 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.
• Lead and 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, when escalation is appropriate, and while providing guidance to others on analytic approaches and guidelines.
• 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 participating in client meetings and conference calls, explaining statistical concepts, presenting analytic findings, and serving as a trusted analytic advisor.
• Work cross-functionally with internal teams, including Client Services, Data Acquisition & Performance, Modeling/Statistics, 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; proactively identify and surface risks before they impact delivery; help drive alignment across collaborator groups; and facilitate consensus on analytic recommendations and project approaches.
• Support the development of peers through mentoring, knowledge sharing, training, and collaboration, contributing to team learning, skill development, and continuous improvement.
• Write new Python (and PySpark, where applicable) code, enhance and maintain existing codebases, apply relevant industry techniques and trends, evaluate emerging analytic approaches and technologies, and provide recommendations for improvements to modeling methodologies and analytic workflows.
• Ensure compliance with applicable privacy, data governance, and AI guidelines across all…