Data Science Manager (Growth Analytics)

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 are looking for a Product Analytics Manager to lead analytics for Cleo’s Product Growth pillar
• Our Growth pillar works across acquisition, onboarding, conversion, retention and expansion into new markets. You will lead a team of 4 to 5 Product Analysts who are embedded in cross functional squads across these areas. Your team’s work will directly influence how we acquire, convert and retain users, how we improve payback and LTV, and how we scale Cleo to millions more people in a sustainable way
• You will work alongside leaders in Analytics, Product, Engineering, Marketing and Design, you will play a strategic decision making role in one of Cleo’s most important levers. You will set the bar for growth analytics at Cleo, while staying hands on and delivering high impact analysis yourself
• 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
• 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
• 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
• 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

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