Head of Data Science, Credit Risk Analytics

Meet the team 👥

Here at Cleo we have team of ~135 member in our Borrow Pillar and ~8 dedicated to Credit Policy and Analytics. This function brings together several specialisms, all working toward managing portfolio performance; designing the systems, models, and controls that make lending sustainable. They drive to build and grow a portfolio of responsible EWA & Pay Later products that can scale across markets while protecting users from high cost debt trap.

About the role ✍️

We're hiring a Head of Data Science to lead credit performance measurement and monitoring within our Risk & Payments pillar. This is a player-coach role: you'll manage a team of Credit Data Scientists and Analysts, splitting your time between hands-on analysis and leading the team - setting direction, developing people, and owning the function's output.

You'll own the frameworks and metrics that keep our credit products healthy, and drive the deep-dive analyses that explain performance shifts and turn them into action. Key areas of impact:

• Own credit performance measurement - design and maintain Cleo's risk metric framework (arrears, default, yield, LTV, marginal loss), and the dashboards/alerts that catch arrears spikes, roll-rate shifts, and decisioning anomalies early.

• Bridge model health and business decisions - partner with Risk Modelling to translate model metrics (AUC, PSI, calibration, drift) into policy and product recommendations, and diagnose whether performance moves are model-driven, macro, or operational.

• Lead root-cause analysis - own investigations end-to-end (question → analysis → recommendation) on issues like arrears spikes or yield compression, using driver analysis (SHAP, feature importance, decomposition), and present findings to Risk, Product, and Leadership.

• Support policy and decisioning - work with Credit Policy and Decision Science to build evaluation frameworks for policy changes, quantify their marginal impact, and support elasticity/profitability modelling on pricing and limits.

• Manage and develop a team - directly manage Credit Data Scientists and Analysts: set priorities, manage performance, and grow the team, not just direct project work.

What we're looking for 🕵️

• Strong SQL and Python skills, comfortable working directly from the warehouse

• Track record owning analyses end-to-end - from framing the question to shipping a recommended change

• Hands-on experience with predictive models (credit, fraud, or similar), fluent in AUC/Gini, calibration, PSI/CSI, and drift

• Fluency in credit portfolio metrics (arrears buckets, roll rates, loss rate, yield/marginal loss) and how they tie to unit economics

• Experience directly managing analysts or data scientists - priorities, performance, and people development

• Nice to have: experience with short-term or revolving credit products

• Nice to have: experience with both UK and US regulatory frameworks

What we offer

We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements.

For the full breakdown on what's available in your location, visit our Candidate Hub 👈