Data Science

IndusInd Bank; Mumbai; On-site; INR 3,500,000 - 5,200,000; Full time

Job summary

IndusInd Bank is seeking a senior analytics leader to own and define credit risk strategy across retail lending, oversee end-to-end model lifecycle including IFRS 9/ECL, and drive portfolio analytics and performance management.

You will implement enhanced risk controls, STP frameworks, and robust model risk management, partner with cross-functional teams, and present insights to leadership while ensuring regulatory compliance.

Qualifications

• Experience in data science and credit risk analytics.
• Exposure to bank, NBFC, or fintech portfolios.
• Strong analytical and governance skills.

Responsibilities

• Own and define the credit risk strategy and risk appetite framework across retail lending portfolios.
• Oversee the end-to-end model lifecycle for multiple models (Application, Behavioral, Collections, IFRS 9/ECL).
• Drive portfolio analytics and performance management through monitoring of vintages, delinquencies, losses, and trends.
• Recommend enhancements to credit policies, underwriting frameworks, and decision criteria.
• Build and enhance automated decisioning and STP frameworks leveraging bureau/open data.
• Establish robust model risk management practices including validation and drift detection.
• Partner with Business, Product, Technology, Data Engineering, and Operations teams.
• Present portfolio insights and model outcomes to senior leadership and risk committees.
• Ensure compliance with regulatory, governance, and audit requirements.
• Drive risk transformation and innovation in data infrastructure and decision engines.
• Lead, mentor, and develop analytics and risk teams.

Skills

Credit risk strategy

Model lifecycle

Portfolio analytics

Policy enhancements

Decisioning & STP

Model risk mgmt

Stakeholder alignment

Executive reporting

Regulatory compliance

Risk transformation

Team leadership

Statistics/ML

Education

Bachelor's degree in Statistics/Mathematics/Economics/Engineering/Quantitative Finance or Management

Master’s degree in Statistics/Mathematics/Economics/Engineering/Quantitative Finance or Management

Job description

• Own and define the credit risk strategy and risk appetite framework across retail lending portfolios ensuring alignment with business objectives and long-term risk tolerance.
• Oversee the end-to-end model lifecycle for Application, Behavioral, Collections, and IFRS 9/ECL models, including development, governance, validation, implementation, and ongoing performance optimization.
• Drive portfolio analytics and performance management through continuous monitoring of acquisition quality, vintages, delinquencies, losses, credit costs, early warning indicators, concentration risks, and emerging portfolio trends.
• Recommend enhancements to credit policies, underwriting frameworks, and decision strategies by translating analytical insights into actionable risk controls, customer segmentation, approval criteria, exposure management, and portfolio optimization initiatives.
• Build and enhance automated decisioning and Straight-Through Processing (STP) frameworks, leveraging bureau data, open banking data, alternative data sources, and advanced analytics to improve risk-adjusted growth and customer experience.
• Establish robust model risk management practices, including model validation, performance monitoring, drift detection, periodic recalibration, redevelopment, documentation, governance, and audit readiness.
• Partners with Business, Product, Technology, Data Engineering, and Operations teams to evaluate growth opportunities, implement risk strategy changes, optimize customer acquisition, and enhance portfolio profitability.
• Present portfolio insights, model outcomes, stress-testing results, and strategic recommendations to senior leadership, management committees, board-level forums, and risk governance committees.
• Ensure compliance with regulatory, governance, and audit requirements, including RBI guidelines, model governance standards, IFRS 9 requirements, internal audits, and external regulatory reviews.
• Drive risk transformation and innovation initiatives by improving data infrastructure, analytical capabilities, decision engines, monitoring frameworks, and end-to-end credit lifecycle processes.
• Lead, mentor, and develop high-performing analytics and risk teams, fostering technical excellence in statistics, machine learning, risk modelling, portfolio analytics, and strategic decision-making.

EDUCATION

- Bachelor's degree in Statistics, Mathematics, Economics, Engineering, or quantitative Finance or Management

Preferred:

Master’s degree from Statistics, Mathematics, Economics, Engineering, or quantitative Finance or Management

- 10+ years of progressive experience in data science, Credit risk analytics, with a clear track record of owning portfolio risk in a bank, NBFC, or fintech.