Head Of Data Science, Credit Risk Analytics

About Cleo
About The CompanyAbout Cleo: At Cleo, we're not just building another fintech app.
We're embarking on a mission to fundamentally change humanity's relationship with money.
Imagine a world where everyone, regardless of background or income, has access to a hyper-intelligent financial advisor in their pocket.
Cleo is a rare success story: a profitable, fast-growing unicorn with over $300 million in ARR and growing over 2x year-over-year.
This isn't just a job;
it's a chance to join ateam of brilliant, driven individuals who are passionate about making a real difference.
We have an exceptionally high bar for talent, seeking individuals who are not only at the top of their field but also embody our culture of collaboration and positive impact.
If you're driven by complex challenges that push your expertise, the chance to shape something truly transformative, and the potential to share in Cleo's success as we scale, while growing alongside a company that's scaling fast, this might be your perfect fit.
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About The RoleWe'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 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: Manage and mentor Credit Data Scientists/Analysts, setting clear priorities and deliverables.
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 ForExperience & 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