IndusInd Bank - Risk Analytics Lead - Business Intelligence Unit

Overview:
- The Risk Analytics Lead will be responsible for driving portfolio monitoring, data driven underwriting strategies, and portfolio management analytics across the lending lifecycle.
- This role requires deep expertise in risk metrics, bureau data, and advanced analytics, along with strong programming capabilities to analyze large scale datasets. The incumbent will play a critical role in strengthening credit quality, optimizing growth, and proactively managing portfolio risk.
Key Responsibilities:
Portfolio Monitoring & Risk Oversight:
- Own end to end portfolio monitoring across products, vintages, cohorts, and customer segments.
- Track, analyze, and interpret key risk and performance metrics including delinquency, roll rates, vintage curves, loss rates, LGD, EAD, and early warning indicators.
- Identify emerging risk trends and proactively flag deterioration in portfolio health.
- Design and maintain dashboards and monitoring frameworks for senior management and risk committees.

Data Driven Underwriting & Portfolio Strategies:
- Develop and refine data driven underwriting strategies to balance risk and growth.
- Support score thresholds and rule based decision frameworks.
- Perform scenario analysis and impact assessments for policy or strategy changes.
Programming & Advanced Analytics:
- Use strong programming skills (Python / SQL / R) to run complex analysis on large volume datasets.
- Work closely with data engineering and technology teams to productionize analytics where required.
Stakeholder Collaboration:
- Partner with Risk, Business, and Product teams to translate analytics into actionable decisions.
- Present insights and recommendations clearly to senior stakeholders and leadership forums.
Required Qualifications & Skills:

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- Bachelor's or Master's degree in Statistics, Mathematics, Economics, Engineering, Data Science, or related fields.
- 6-8+ years of experience in risk analytics, preferably within lending, NBFCs, fintech, or banking.
- Strong hands on expertise in portfolio analytics, underwriting analytics, and credit risk management.
- Deep understanding of bureau data and credit behavior.
- Excellent programming skills in Python and SQL.
- Ability to work with large, complex datasets and deliver high quality insights.
Preferred Experience:
- Experience across retail / SME / unsecured lending portfolios.
- Exposure to model monitoring, scorecard performance tracking, or policy analytics.
- Strong communication skills with the ability to influence data driven decision making.