At a Glance
- Tasks: Lead a team of data scientists to enhance credit performance and drive impactful analyses.
- Company: Join Cleo, the innovative AI financial assistant transforming money management for everyone.
- Benefits: Enjoy equity, health insurance, mental health support, and a paid sabbatical after four years.
- Other info: Diverse and inclusive workplace committed to fair hiring practices.
- Why this job: Make a real difference in how people interact with their finances while leading a talented team.
- Qualifications: Strong SQL and Python skills, experience in predictive modelling, and team management.
The predicted salary is between 75600 - 92400 £ per year.
Most money apps talk at you. Cleo talks back. We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process for everyone, whatever their background or balance. The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money.
Here at Cleo we have a team of ~135 members 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 traps.
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 a 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.
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 merits. 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.
Head of Data Science, Credit Risk Analytics employer: Cleo
Cleo is an exceptional employer that fosters a collaborative and innovative work culture, where your contributions directly impact the development of cutting-edge AI solutions. With a strong emphasis on employee growth, you will have ample opportunities to mentor and lead talented teams while working in a dynamic environment that values creativity and forward-thinking. Located in a vibrant tech hub, Cleo offers unique advantages such as access to industry-leading resources and a supportive community that champions professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Data Science, Credit Risk Analytics
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Cleo.
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When you find a suitable opening like Head of Data Science, Credit Risk Analytics at Cleo, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Head of Data Science, Credit Risk Analytics
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Cleo, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cleo. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Cleo
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Cleo!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.