Head of Data Science, Credit Risk Analytics

Cleo; United States; Hybrid; USD 111,296 - 144,319; Full time

Benefits offered by this job

Competitive compensation package

Clear progression plan

25 days annual leave plus public holidays

Enhanced parental leave

Job summary

Cleo is looking for a Head of Data Science to lead the credit performance measurement and monitoring. You will be responsible for the design of risk metrics and data-driven decisions to optimize credit products.

The ideal candidate has strong analytical skills, fluency in SQL and Python, and experience with predictive models. This role supports a fast-growing tech startup with a flexible working environment and competitive compensation.

Qualifications

• Strong analytical skills with fluency in SQL and Python.
• Experience conducting large-scale A/B experiments.
• Fluent in credit portfolio metrics like arrears buckets and loss rate.

Responsibilities

• Own the design and maintenance of the credit risk metric framework.
• Partner with Risk Modelling to translate model health metrics.
• Lead root-cause analysis for key metric deteriorations.

Skills

Analytical skills with fluency in SQL

Fluent in Python

Experience with A/B experiments

Knowledge of credit portfolio metrics

Experience with predictive models

Job description

About Cleo

At Cleo, we are building a hyper‑intelligent financial advisor in your pocket, aimed at providing access to financial services for everyone, regardless of background or income. With over £300 million in annual recurring revenue and more than 2× year‑over‑year growth, we’re a profitable, fast‑growing unicorn scaling fast across the UK and the US.

About the Role

As Head of Data Science for Credit Performance, you will lead the measurement, monitoring and optimisation of Cleo's credit risk framework. You’ll own the design of risk metrics, maintain the monitoring dashboards and drive data‑driven decisions that keep our credit products healthy and profitable.

Key Responsibilities

• Credit Performance Measurement & Monitoring: Own the design and maintenance of the credit risk metric framework, including arrears, default, yield, LTV and marginal loss rates; build dashboards and alerts for early detection of shifts.
• Model Understanding & Monitoring: Partner with Risk Modelling to translate model health metrics into actionable policy or product recommendations; detect and diagnose feature drift and separate model‑driven changes from operational causes.
• Analytical Deep‑Dives: Lead root‑cause analysis for key metric deteriorations and deliver driver analysis using SHAP, feature importance or decomposition; quantify the risk‑adjusted impact of product changes.
• Policy & Decisioning Support: Define evaluation frameworks for policy changes, quantify marginal impact of shifts, and support elasticity and profitability modelling for amounts, pricing and feature‑level decisioning.
• Team Leadership & Stakeholder Management: Directly manage a team of Credit Data Scientists and Analysts, set priorities, develop people, translate findings to senior leadership and build cross‑functional relationships with Commercial, Product, Data Science and Finance.

Qualifications

• Strong analytical skills with fluency in SQL and Python.
• Background 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—arrears buckets, roll rates, loss rate, yield/marginal loss—and how they tie to unit economics and P&L.
• Hands‑on experience building and maintaining performance monitoring systems and alerting frameworks.
• Experience working with predictive models (credit, fraud, marketing), interpreting metrics like AUC, calibration, PSI, drift.
• Track record of taking analyses end‑to‑end and delivering measurable impact.
• Experience directly managing a team—setting priorities, managing performance and developing people.
• Skilled at translating technical analysis into actionable recommendations for senior stakeholders.

Nice to Have

• Familiarity with short‑term or revolving credit products.
• Experience working with both UK and US regulatory frameworks.

Benefits

• Competitive compensation package (base + equity) with 3‑annual reviews.
• Salary banding: £116,510‑£144,319 UK, London Hybrid / £111,296‑£139,273 UK, Remote.
• Work at a fast‑growing tech startup backed by top VC firms.
• Clear progression plan and flexible working arrangements.
• Company‑wide performance reviews every 4 months and generous pay increases for high‑performing team members.
• Equity top‑ups for promoted team members, 25 days annual leave + public holidays plus an extra day for every year at Cleo (up to 30 days).
• 6% employer‑matched pension in the UK and Private Medical Insurance via Vitality.
• Enhanced parental leave, 1 month paid sabbatical after 4 years, workplace nursery scheme and regular socials.

We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers and people from lower socio‑economic backgrounds. If there’s anything we can do to accommodate your specific situation, please let us know.