Role Overview :
We are seeking an experienced Credit Risk Strategy Analyst to support and enhance our risk decisioning, portfolio performance, and credit lifecycle strategies. The ideal candidate will have strong expertise in banking risk , advanced SQL / Python skills, and hands-on experience with data visualization tools . This role involves evaluating credit performance, developing risk frameworks, and enabling data-driven insights that strengthen underwriting, portfolio monitoring, and collections strategies.
Key Responsibilities :
- Design, implement, and optimize credit risk strategies across the customer lifecycle, including acquisition, underwriting, account management, and collections.
- Conduct detailed risk analysis to identify trends, portfolio health indicators, and early warning signals.
- Develop dashboards and performance reports using visualization tools (Power BI, Tableau, etc.) to support strategic decision-making.
- Use SQL and Python to extract, manipulate, analyze, and model large datasets from multiple banking and risk systems.
- Partner with product, policy, analytics, and compliance teams to refine decision rules and strengthen risk governance.
- Support the creation of risk scorecards and segmentation frameworks for improved credit decisioning.
- Evaluate performance of existing strategies and recommend enhancements based on data-driven insights.
- Ensure compliance with internal risk policies, regulatory expectations, and audit requirements.
- Document analytical outputs, methodologies, and recommendations for leadership review.
Required Skills & Experience :
4–8 years of experience in Credit Risk Strategy , Banking Risk, or Risk Analytics.Strong proficiency in SQL for data extraction and transformation.Hands-on experience with Python for analytics, modeling, and automation.Proficiency in data visualization tools (Power BI, Tableau, or equivalent).Solid understanding of credit lifecycle , risk KPIs, and banking risk concepts.Experience working with financial, credit bureau, and behavioral datasets.Strong analytical thinking, problem-solving skills, and stakeholder communication abilities.Preferred Qualifications :
Experience in retail lending, digital lending, credit cards, BNPL, or personal loans .Knowledge of risk decision engines , strategy deployment, or rules configuration.Familiarity with regulatory frameworks (RBI guidelines, Basel norms, credit risk governance).Background in statistics, finance, economics, mathematics, or data science .