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Metro location, mid-level generalist data title, broad required skillset, and recognizable brand increase applicant competition.
Technical analytics skills transfer across industries, but marketing/data-product domain knowledge increases fit specificity.
Explicit 5+ years plus mandatory statistical methods, Python/PySpark/SQL and client-facing experience raises strictness.
Deliver accurate, timely statistical analysis and modeling support for assigned client projects and internal initiatives.
Independently design, implement, validate, and present analytic projects using established statistical methods and tools (Python, PySpark, SQL).
Collaborate cross-functionally and directly with clients to provide consulting, troubleshoot issues, and improve analytic workflows and systems.
5+ years of professional experience, with minimum 3 years in a statistical field involving data analysis or modeling at scale.
Bachelor's degree in statistics, quantitative or related field required; advanced degree preferred.
Proficiency in Python (and PySpark where applicable), SQL, Excel, PowerPoint, and advanced knowledge of statistical methods (regression, clustering, ANOVA, etc.).
Experience working directly with external clients in a business environment; familiarity with Epsilon data products and direct marketing concepts preferred.
Experienced individual contributor with ability to independently manage multiple analytic projects end-to-end under minimal oversight.
Skilled in applying advanced statistical modeling techniques and developing/maintaining analytic codebases in Python and SQL.
Consultative communicator able to clearly explain complex analytic concepts to both technical and non-technical stakeholders and collaborate cross-functionally.