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Tier-1 brand, mid-level generalist ML role, metro location, and common skillset create high competition.
Core ML and analytics skills are transferable across industries, though banking domain knowledge moderately reduces fit.
Explicit 5+ years, master's degree requirement, and technical skill expectations create high shortlisting strictness.
Lead complex, cross-functional data science initiatives by applying advanced analytical, statistical techniques to generate actionable insights and strategic recommendations.
Analyze and resolve large-scale, multi-faceted business and operational challenges using in-depth hypothesis generation and advanced analytics.
Collaborate with mid to senior managers to influence business decisions, lead projects or teams, and mentor peers in data science best practices.
5+ years of data science experience or equivalent demonstrated through work, training, military experience, or education.
Master's degree or higher in quantitative discipline (mathematics, statistics, engineering, physics, economics, or computer science).
Experience with advanced analytics modeling and programming; specific languages/tools (SQL, Python, SAS, GCP, Tableau/Power BI/Excel) mentioned as desired but not strict requirements.
Work Experience Required: 5+ years data science experience.
Experience working on strategic analysis including customer profiling, business segmentation, heuristics, inferential statistics, and RFM analysis.
Proficiency in machine learning techniques such as segmentation, regression, decision trees, forecasting, and clustering.
Ability to manage multiple tasks in a dynamic environment, communicate complex data insights clearly to non-technical audiences, and guide others on data science methods.