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Tier-1 employer, metro location, mid-level data science title, and broad technical requirements increase competition.
Core data science skills transfer across industries, but banking domain and risk knowledge moderately constrain fit.
Explicit 5+ years, advanced degree preference, and specific technical/ML/GCP skills create strict screening filters.
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Lead complex data science initiatives using advanced analytical and statistical techniques to generate actionable insights and recommendations with broad cross-functional impact.
Make data-driven decisions in complex business situations and lead teams to meet deliverables and drive new data science initiatives.
Collaborate with mid-to-senior managers and peers to provide strategic analytical consulting and communicate insights effectively to non-technical audiences.
5+ years of data science experience demonstrated by work, training, military experience, or education.
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
Proficiency in SQL, Python, and SAS required; experience with Google Cloud Platform and BI tools like Tableau, Power BI, or Excel is desired.
Work Experience Required: 5+ years in data science.
Experienced in building strategic analyses using customer profiling, business segmentation, heuristics, and inferential statistics (e.g., RFM analysis).
Proficient with machine learning techniques such as segmentation, regression, decision trees, forecasting, and clustering.
Capable of managing multiple priorities in dynamic environments and effectively communicating analytical insights to diverse stakeholders.