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Tier-1 bank, metro location, mid-level generalist data role with broad skills, high applicant competition.
Core data science skills are transferable, but banking risk/compliance context creates moderate domain specificity.
Mandatory 4+ years and advanced degree preference at a regulated bank increases strictness of candidate filtering.
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Lead or participate in moderately complex data science projects using advanced analytical, statistical techniques, and machine learning to generate actionable insights and strategic recommendations.
Review and analyze large structured and unstructured data sets to convert data into meaningful business insights and resolve moderately complex issues independently or as a team lead.
Communicate data-driven recommendations effectively to non-technical audiences and may mentor junior staff or lead project teams.
4+ years of data science experience (work experience, training, military experience, or education).
Master's degree or higher in quantitative discipline (mathematics, statistics, engineering, physics, economics, computer science).
Proficiency in SQL, Python, SAS, PySpark; experience with GCP and BI tools (Tableau, Power BI, Excel).
Experience with machine learning methods (segmentation, regression, decision trees, forecasting, clustering).
Experienced in handling moderately complex data science initiatives involving both structured and unstructured data in dynamic environments.
Skilled in applying strategic analysis techniques including customer profiling, business segmentation, heuristics, inferential statistics, and RFM analysis.
Capable of managing multiple priorities, leading teams or projects, and communicating insights to varied audiences including mentoring lower-level staff.