Job Description

Main Accountabilities

Qualifications & Experience

• Post Graduate degree with a background in Statistics / Mathematics / Economics/ Engineering / MBA from premier institutes
• Experience of 3-6 years in the field

Functional Competencies

• Hands on experience with scoring/data modelling
• Tools: Python & SQL
• Statistical Techniques: Logistic Regression, Segmentation, Forecasting, Machine Learning Techniques, Optimization.

• Monitor and analyze portfolio performance for Personal Loans (PL) and Business Loans (BL), including delinquency trends, vintage analysis, segment-wise performance, and risk triggers.
• Conduct offer validation and performance analysis using Python, SQL, and data analytics tools to ensure optimal customer acquisition and portfolio quality.
• Evaluate alternative and bureau-based data sources, conduct Proof of Concepts (POCs), and recommend data-driven strategies to enhance credit underwriting and risk assessment.
• Track, measure, and assess the effectiveness of implemented risk strategies, scorecards, underwriting rules, and portfolio management initiatives.
• Collaborate closely with the Risk, Policy, Product, Business, and Data Science teams to evaluate, approve, implement, monitor, and periodically recalibrate risk models, scorecards, and decisioning frameworks based on portfolio performance.
• Lead and manage cross-functional Risk Analytics and Risk Transformation projects, ensuring timely implementation and achievement of business objectives.
• Perform customer segmentation, cohort analysis, champion-challenger testing, and strategy impact assessment to drive continuous portfolio optimization.
• Support policy formulation and risk governance through data-backed insights, analytics, and recommendations.

• Drive automation initiatives in portfolio monitoring, risk reporting, and analytical processes to improve efficiency and decision-making.