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Tier-1 brand, metro location, mid-level generalist data role, and popular title increase competitiveness.
Data science skills are transferable, but banking risk/compliance focus adds moderate domain specificity.
Explicit 4+ years, preferred master's, and mandatory tools (SQL/Python/GCP) create strict filters.
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Lead or participate in data science initiatives using advanced analytics, statistical techniques, and models to deliver actionable insights and influence business strategies.
Analyze large, complex structured and unstructured data sets to generate hypotheses and recommendations that impact broader planning and decision-making.
Collaborate with teams and mid-level managers, potentially leading projects or mentoring staff, to drive data-driven recommendations and solutions for business problems.
4+ years of data science experience or equivalent through education, training, or military experience.
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
Experience with data analysis, advanced analytics modeling, and communicating actionable insights to non-technical audiences.
Not explicitly mentioned in the JD: notice period or location constraints.
Proficient in SQL, Python, SAS, and PySpark with hands-on experience in Google Cloud Platform (GCP).
Experienced with BI tools such as Tableau, Power BI, or Excel and skilled in customer profiling, business segmentation, and inferential statistics.
Able to manage multiple priorities in a dynamic environment with good organizational and communication skills and knowledge of machine learning techniques like segmentation, regression, decision trees, forecasting, and clustering.