About the role
We are looking for an experienced Credit Risk Strategy professional with 3+ years of experience in designing and optimising 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
The candidate will have responsibilities across the following functions:
Underwriting Strategy and Credit Risk:
- Design, implement, and optimise 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.
- Analyse performance of existing strategies (vintages, cohorts, segments) and recommend data-driven enhancements.
- Use SQL and Python to extract, transform, and analyse large datasets from multiple internal, bureau, and third-party sources.
Fraud Risk (First-Party Focus):
- Identify and analyse first-party fraud patterns and behaviours across the credit lifecycle.
- Design and implement rules, flags, and strategies to detect and prevent first-party fraud while minimising impact on genuine customers.
- Partner with operations, collections, and product teams to refine fraud controls and feedback loops.
Requirements:
- 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 modelling; 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.