Head of Credit Risk & Data Science

About the role

FINN, a fintech founded in 2022 that gives underbanked employees access to wages they have already earned, is looking for a Head of Credit Risk to own and lead its credit risk strategy, underwriting policies and portfolio performance. This is a senior risk leadership role focused on balancing sustainable growth, responsible lending and portfolio profitability, and it combines credit risk with data science and machine learning.

Key responsibilities

• Own the credit risk strategy, risk appetite, underwriting policies and approval frameworks, and partner with Finance on expected credit loss modeling and provisioning
• Monitor portfolio performance (delinquency, roll rates, default and loss rates) and set up early warning systems and stress testing
• Own the end-to-end underwriting strategy, including eligibility, credit assessment, approval rules and risk-based decisioning, and run controlled experiments to test policy changes
• Apply data science and machine learning to credit scoring, underwriting, risk segmentation and fraud detection, and define model requirements, validation, monitoring and interpretability
• Lead a team of risk analysts and data scientists, and build a clear risk governance framework and reporting for executive leadership

Required profile

• At least 10 years of relevant experience across credit risk, consumer lending, credit analytics or data science, with proven leadership of credit risk strategy and consumer credit portfolios
• Proven ownership of credit policies, underwriting frameworks and risk appetite in fintech, digital lending, consumer finance, BNPL or digital banking
• Experience managing credit risk across multiple products, customer segments or markets, and leading teams of risk professionals and data scientists
• Bonus: experience in Southeast Asian credit markets, earned wage access, IFRS 9 expected credit loss modeling, and launching credit products in new markets

Required skills

• Credit risk metrics, portfolio monitoring, delinquency trends, loss forecasting and risk mitigation
• Credit scoring, statistical modeling and machine learning applied to underwriting and decisioning
• Ability to evaluate ML-based credit models and guide their development and deployment
• Strong analytical, quantitative and commercial judgment, and excellent communication with senior stakeholders

What we offer

• Competitive compensation based on experience and location
• Equity participation
• The chance to build and shape the credit risk function from the ground up