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Tier-1 employer, metro location, and mid-level generalist Data Scientist title increase applicant competition.
Role explicitly requires home-loans/retail lending experience, making industry background highly important.
Explicit 4-5 years, lending domain experience, and mandatory ML/BI tech stack make shortlisting strict.
Develop and deploy predictive models to optimize business decisions in loan approvals, collections, and risk management areas such as NPA prediction and ECL provisioning.
Create and automate data visualization dashboards and reports using Power BI for monitoring portfolio health, customer behavior, and operational metrics.
Collaborate with stakeholders to align analytics solutions with business objectives and deliver complex ad-hoc analyses for process, sales, and underwriting optimizations.
4-5 years of experience in Home Loans, Retail Lending products, or related financial services industry.
Proficient with Python data science libraries (NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow) and MySQL database querying.
Hands-on experience in designing and developing automated, visually appealing dashboards using Power BI.
Graduate degree in Statistics, Mathematics, Analytics, Computer Science, or related field.
Experienced in applying machine learning and statistical techniques specifically within retail lending or home loan analytics domains.
Skilled in end-to-end analytical product delivery including predictive and prescriptive analytics for commercial impact.
Comfortable interfacing with cross-functional teams and leadership to translate business needs into actionable analytics solutions.