Head of Data Science, Credit Risk Analytics

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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 looking for a Data Science Manager 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.

This role is not for you if...

• Your experience is mainly credit policy / underwriting with light analysis support.
• Your primary tools are Excel, SAS, or Access, and you rarely write SQL yourself.
• You're looking for a risk policy or regulatory role rather than hands-on analytics.
• You've never had direct reports and are looking to step into people management for the first time.

Interview Process

• Recruiter Interview (30 mins)
• Hiring Manager Interview (30 mins)
• Technical Interview (60 mins)
• Whiteboard Interview (60 mins)
• Leadership & Comms Interview (60 mins)

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, dental and vision insurance, mental health support, a paid one-month sabbatical after four years, a learning and 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

What Matters

Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their metris.

We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know.

We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!

Compensation Range: £87K - £145K