Job Role : Manager/Lead - Credit Risk Strategy

Years of Experience : 3 to 15 Years

Job Summary :

We are looking for an experienced Credit Risk Strategy professional with 3+ years of experience in designing and optimizing underwriting strategies using bureau and third- party data. The ideal candidate will have hands-on experience in credit decisioning, portfolio performance analysis, and first-party fraud risk management

Key Responsibilities :

Underwriting Strategy & Credit Risk :

- Design, implement, and optimize credit underwriting strategies across the customer lifecycle (originations, line management, renewals, etc.) using bureau and third party data.

- Develop and refine credit decision rules, cut-offs, and segmentation strategies to balance growth, risk, and profitability.

- Analyze performance of existing strategies (vintages, cohorts, segments) and recommend data-driven enhancements.

- Use SQL and Python to extract, transform, and analyze large datasets from multiple internal, bureau, and third- party sources.

Fraud Risk (First-Party Focus) :

- Identify and analyze first-party fraud patterns and behaviors across the credit lifecycle.

- Design and implement rules, flags, and strategies to detect and prevent first-party fraud while minimizing impact on genuine customers.

- Partner with operations, collections, and product teams to refine fraud controls and feedback loops.

Required Qualifications :

- Bachelor's or Master's degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.

- 3-6 years of hands-on experience in credit risk / underwriting strategy within banking, NBFC, fintech, or credit risk consulting.

- Demonstrated experience in designing and implementing underwriting strategies using credit bureau data (e.g., CIBIL, Experian, Equifax, CRIF) and third- party data sources

Strong proficiency in :

- SQL - advanced querying, joins, aggregations, performance tuning for large datasets.

- Python - data manipulation (pandas), analysis, and basic modeling; ability to productionize or hand over code to engineering teams.

- Strong analytical and problem-solving skills with the ability to translate data insights into actionable strategies.

- Excellent communication skills with the ability to present complex analyses and recommendations to non-technical stakeholders.