Vice President Data Science

Role & responsibilities

We are seeking an experienced Credit Risk professional with 10+ years of experience in Credit Risk Modelling, Portfolio Analytics, and Risk Strategy. The role will be responsible for driving end-to-end credit risk strategy across the customer lifecycle including model development, monitoring and deployment, portfolio management, IFRS 9/ECL analytics, and other data science initiatives. The incumbent will partner with Business, Risk and Technology teams to optimize portfolio profitability while maintaining acceptable risk levels and regulatory compliance.

• 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.

Preferred candidate profile

Essential requirements:

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

Preferred:

Masters degree from Statistics, Mathematics, Economics, Engineering, or quantitative Finance or Management

Essential requirements:

- 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.

Desired Behavioral / Functional Traits

Functional Traits:

• Credit Risk Strategy & Portfolio Management: Ability to define risk appetite, optimize portfolio performance, and balance growth, profitability, and risk.
• Risk Modelling Expertise: Strong experience scorecards development, stress testing, model governance, and validation.
• Advanced Analytics & Decisioning: Expertise in statistics, machine learning, portfolio analytics, automated decisioning, and risk policy design.
• Regulatory & Governance Knowledge: Deep understanding of RBI regulations, IFRS 9, model risk management, and audit/compliance requirements.
• Business & Stakeholder Management: Ability to translate analytical insights into business strategy and influence senior leadership decisions.

Desired Behavioural Traits:

• Strategic Thinker: Anticipates emerging risks and aligns risk strategy with long-term business objectives.
• Strong Leadership: Builds, mentors, and develops high-performing analytics and risk teams.
• Influential Communicator: Effectively presents complex analytical insights to senior stakeholders and governance forums.
• Change & Innovation Driven: Champions transformation, automation, and data-driven decision-making across the credit lifecycle.