About The Role
We're looking for a Head of Data Science to lead the measurement, monitoring, and optimisation of Cleo's credit performance. This is a high-impact role at the heart of how we manage risk and drive sustainable growth. You'll own the frameworks, metrics, and deep-dive analyses that keep our credit products healthy and ensure that when performance shifts, we understand why and act quickly.
Sitting within the Risk & Payments pillar, you'll lead a team of analysts to deliver clear, actionable insights across arrears, yield, LTV, and portfolio performance, working closely with Credit Policy, Decision Science, Product, and Finance. You'll be setting the measurement standards for the company, diagnosing portfolio trends, and shaping how we evaluate and implement policy changes.
This is a player-coach role: the best candidate brings both genuine technical depth and the people management expertise to lead a high-performing team around them. You'll split your time between hands-on analysis and leading the team; setting direction, developing people and owning the function's output.
This role is ideal for someone who thrives at the intersection of data, systems thinking, and stakeholder influence. You'll be equally comfortable explaining SHAP outputs to a data scientist, talking loss economics with finance, and summarising driver analysis for senior leadership.
Key Responsibilities
Credit Performance Measurement & Monitoring:
- Own the design and maintenance of Cleo’s credit risk metric framework, including arrears, default, yield, LTV, and marginal loss rates.
- Build and maintain dashboards and alerts for early detection of arrears, roll-rate shifts, and decisioning anomalies.
- Ensure definitions, thresholds, and escalation processes are consistent, documented, and used company-wide.
Model Understanding & Monitoring
- Partner with the Risk Modelling team to turn model health metrics (AUC, PSI, calibration, feature drift) into clear recommendations for policy or product changes.
- Detect and diagnose feature shift or concept drift, ensuring model inputs remain valid and predictive.
- Lead investigations into performance deviations, separating model-driven changes from macro or operational causes.
Analytical Deep-Dives
- Lead root cause analysis for deterioration in key metrics such as arrears spikes or yield compression.
- Own investigations from question → analysis → recommendation, and present your work to Risk, Product, and Leadership.
- Deliver driver analysis (SHAP, feature importance, decomposition) for changes in portfolio performance.
- Quantify the risk-adjusted impact of new or changing product features on portfolio health.
- Design and analyse multivariate experiments on underwriting, pricing, or repayment flows, and translate results into actionable risk strategies.
Policy & Decisioning Support
- Partner with Credit Policy and Decision Science to design robust evaluation frameworks for policy changes.
- Quantify the marginal impact of policy shifts, controlling for macro or seasonal effects.
- Support elasticity and profitability modelling to optimise amounts, pricing, and feature-level decisioning.
Team Leadership & Stakeholder Management
- Directly manage a team of Credit Data Scientists and Analysts — setting priorities, managing performance, and actively developing people, not just directing project work.
- Translate complex analytical findings into clear business implications for senior leadership.
- Build strong cross-functional relationships with Commercial, Product, Data Science, and Finance.
What We’re Looking For
Experience & Skills:
- Strong analytical skills with fluency in SQL and Python.
- Ability to interpret and communicate model performance metrics, feature importance, and confidence intervals.
- Background in collaborating with decision science or data science teams on feature engineering and model evaluation.
- Experience conducting large scale A/B experiments and interpreting results to drive product and business decisions.
- Fluent in credit portfolio metrics – e.g. arrears buckets, roll rates, loss rate, yield/marginal loss – and how they tie to unit economics and P&L.
- Experience building and maintaining performance monitoring systems and alerting frameworks.
- Hands‑on experience working with predictive models (e.g. credit, fraud, marketing), including interpreting metrics like AUC/Gini, calibration, PSI/CSI, drift.
- Experience collaborating with commercial and finance teams on business metric forecasting.
- Track record of taking analyses all the way through to shipped changes and measurable impact.
Leadership & Influence
- Experience directly managing a team of analysts or data scientists — including setting priorities, managing performance, and developing people, not just directing project work.
- Skilled at translating technical analysis into actionable recommendations for senior stakeholders.
- Able to balance short-term monitoring needs with long-term framework building.
Nice To Have
- Familiarity with short-term or revolving credit products.
- Experience working with both UK and US regulatory frameworks.
This role is for you if...
- You spend most of your time in SQL and Python working directly from the warehouse.
- You're used to owning analyses end-to-end — from defining the question, to pulling data, to recommending changes.
- You've worked with predictive models (credit/fraud/propensity/etc.) and think in terms of AUC, calibration, drift, and economics.
- You've managed direct reports before and are comfortable owning both the quality of the team's output and the development of the people producing it.