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Mid-level metro analytics role with broad skills and common title creates high applicant competition.
Core analytics skills are transferable, but marketing/data-product domain knowledge and statistical experience limit cross-industry fit.
Explicit 5+ years, strong statistical methods requirement, plus Python/PySpark/SQL and client-facing skills increases strictness.
Own end-to-end execution and on-time delivery of statistical and analytic projects for assigned clients, ensuring high-quality and well-documented outputs.
Independently build, validate, and present statistical models, research original analytic solutions, and provide clear data-driven recommendations to business and clients.
Collaborate cross-functionally to troubleshoot data, modeling, and process issues; serve as an analytic advisor to clients and internal teams; and contribute to workflow and methodology improvements.
5+ years of experience in statistical or data analysis roles; Bachelor's degree in statistics, quantitative discipline, or related field required; advanced degree preferred.
Proficient in Python (including PySpark where applicable), SQL, Excel, and PowerPoint, with ability to maintain and improve analytic codebases.
Advanced understanding of statistical methods (regression, clustering, factor analysis, ANOVA, etc.) and experience working with large transactional databases.
Experience working directly with external clients in a business environment and familiarity with data products and direct marketing concepts preferred, but not mandatory.
Experienced individual contributor who can independently manage multiple analytic projects end-to-end with minimal supervision and strong attention to detail.
Comfortable working with complex data and statistical modeling methods and communicating findings to both technical and non-technical audiences.
Able to collaborate cross-functionally, support knowledge sharing, and contribute to continuous improvement of analytic workflows and tools within a data-driven environment.