At a Glance
- Tasks: Lead a team of data scientists to drive analytics and experimentation for our AI Financial Assistant product.
- Company: Join Cleo, a dynamic fintech company focused on innovative consumer solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on high-performance and career development.
- Why this job: Make a real impact by shaping user engagement and driving product success.
- Qualifications: 7+ years in data science, strong leadership, and expertise in SQL and Python.
The predicted salary is between 60000 - 80000 £ per year.
Requirements
- 7+ years in product data science / analytics with a track record of improving user and commercial outcomes
- Proven experience in product analytics (e.g., onboarding/activation, conversion funnels, retention) in consumer products
- Experience leading a high‑performing team (at least 2–3 data scientists/analysts; managing a mix of senior and mid-level is a plus)
- Strong influence and communication: You can tell a clear, structured story with data and land insights at the right time to shape decisions. You’ve set/defended targets with senior stakeholders and created broad alignment
- Strong experimentation skills: you’ve designed and interpreted large-scale A/B tests, understand common pitfalls and best practices, and are comfortable guiding others
- Strong SQL and Python skills, and comfort working directly with modern analytics tools and workflows
- You can work end‑to‑end: from defining tracking and metric definitions through to analysis and decision support
- (Desirable) Experience in fintech, personal finance, or high‑growth consumer subscription products
- (Desirable) Experience setting up lightweight analytics standards (metric definitions, experiment reviews, decision frameworks) across multiple squads
What the job involves
We’re hiring a Head of Data Science to own analytics and experimentation for a product pillar at Cleo. You’ll lead a team of 4–5 product data scientists embedded in cross‑functional squads and partner closely with Product, Engineering, Design, and ML leadership to shape what we build. This is a player–coach role: you’ll set the bar for analytics craft across the pillar and stay hands‑on with high‑impact analysis when decisions need to move fast.
You’ll be the analytics leader for the AI Financial Assistant pillar, with a direct line of sight to engagement, revenue, and product roadmap. Your team’s work will directly influence how we acquire, activate, convert, and retain users, improve payback and LTV, and scale Cleo to millions more people sustainably.
Pillar leadership: roadmaps and decision‑making
- Partner with pillar leaders to build a discovery and experimentation roadmap across acquisition, onboarding, conversion, and retention
- Define success metrics, metric trees, and guardrails so squads make consistent, data‑driven decisions
- Support and challenge teams during OKR planning, ensuring initiatives map to clear metrics, realistic targets, and understood trade‑offs
- Provide visibility to senior leadership on pillar performance: what’s driving key metric movement, where the biggest opportunities are, and what we’ll do next
Team leadership: coaching and high performance
- Line‑manage product data scientists, supporting performance, development, and career growth
- Ensure analysts are focused on the highest‑impact work and delivering against pillar priorities
- Coach on stakeholder management, structured problem solving, storytelling, experimentation, and commercial thinking
- Raise the bar for analytics craft through feedback, pairing, templates/playbooks, and lightweight standards that improve quality and speed
Hands‑on analytics and experimentation
- Personally deliver high‑impact analysis that shapes pillar roadmaps and investment decisions
- Deep dive into key metrics to understand trends, root causes, and differences across products and segments
- Own the experimentation program in your pillar: Ensure tests are robust, interpretable, and aligned to strategy. Maintain a test roadmap, prevent collisions, and resolve cross‑team conflicts
- Turn insights into shipped change: align owners and timelines, remove blockers, and close the loop on outcomes
Data foundations
- Champion high‑quality instrumentation, clear metric definitions, and data hygiene
- Work with Analytics Engineering to prioritise modelling needs and ensure the right datasets and definitions exist for your pillar
- Build and oversee dashboards/tools that help squads and leaders act on metrics without always relying on analysts
Head of Data Science (Chat Pillar) employer: Cleo AI
Cleo is an exceptional employer for the Head of Data Science role, offering a dynamic work culture that fosters innovation and collaboration. With a strong emphasis on employee growth, you will lead a high-performing team while having the opportunity to engage directly with cross-functional leaders, shaping impactful decisions that drive user engagement and revenue. Located in a vibrant tech hub, Cleo provides unique advantages such as access to cutting-edge analytics tools and a commitment to data-driven decision-making, making it an ideal place for professionals seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Data Science (Chat Pillar)
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Cleo AI!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Head of Data Science (Chat Pillar) at Cleo AI.
✨Leverage Professional Networks
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 AI.
✨Apply Directly through Our Website
When you find a suitable opening like Head of Data Science (Chat Pillar) at Cleo AI, 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 (Chat Pillar)
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 AI, 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 AI. 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 AI
✨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 AI!
✨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.
