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.