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:

- 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.