Data Scientist / Senior Product Analyst — B2C Subscription (Experimentation & Analytics)

Remote (EU/Ukraine) | Full-time (B2B contract) | Reports to: Head of Data ABOUT THE ROLE OnHires is hiring a Data Scientist on behalf of our client — an established, remote-first B2C SaaS company building a portfolio of subscription products, used by millions of people across 20+ countries. The client is building its data function from the ground up. (Client details shared during the process.) We're looking for someone who lives and breathes experimentation and product analytics in a subscription business — a person who designs rigorous experiments, understands the specific economics of subscriptions (trial conversion, payback, churn, LTV), and turns that into product and revenue decisions. As an early hire on a forming data team, reporting to the Head of Data, you'll help define how experimentation and analytics work here, partnering closely with Product, Growth, and Finance. This is a hands-on, high-ownership role with direct influence on the roadmap. WHAT YOU'LL DO Experimentation & Analytics (the core of the role) - Design, run, and analyse experiments (A/B tests, causal inference, uplift), bringing statistical rigour to how the business measures impact - Own the analysis behind key subscription metrics — trial conversion, churn, retention, LTV, payback — and translate it into clear product and growth decisions - Help shape the experimentation framework and analytics standards as foundations for the wider data team - Bring depth to measurement: variance reduction, significance, and sound experiment design Subscription & Product Insight - Partner with Product, Growth, and Finance to understand the levers behind subscription performance and prioritise what to test - Build the metric logic and definitions the company relies on to make decisions - Turn ambiguous business questions into structured analysis and actionable recommendations Modelling (applied where it drives decisions) - Build and apply predictive approaches where they add value — churn, LTV, propensity — grounded in the realities of the subscription funnel - Partner with Data Engineers to operationalise analysis and models with reliable data pipelines - Handle user-level data responsibly: privacy-aware analysis and compliance with data-use policies WHAT WE'RE LOOKING FOR (MUST-HAVE) - 3+ years in data/product analytics or data science within a B2C SaaS or subscription business — with first-hand understanding of subscription dynamics (trial conversion, churn, LTV, payback, involuntary churn) - Deep experimentation expertise: designing and analysing A/B tests, causal inference, uplift/propensity, with genuine statistical rigour (significance, variance reduction, sound experiment design) - Strong SQL and Python for analysis - Marketing/product analytics experience — comfortable with funnels, cohorts, retention, and monetisation metrics - The ability to turn complex analysis into a clear narrative and a recommendation a non-technical stakeholder can act on - Curiosity and autonomy — comfortable in a fast-moving environment where the roadmap evolves quickly Why the subscription background is essential: churn, LTV, and propensity in a subscription context have very specific dynamics — trial conversion, payback windows, involuntary churn — that shape how you design experiments and interpret results. We're looking for someone who already knows this metric logic, not someone learning it alongside the role. NICE TO HAVE - Experience with predictive modelling in production (churn/LTV/propensity) and the modern ML stack (scikit-learn, etc.) - Familiarity with product analytics tools (Amplitude, Mixpanel, Segment) - Experience building an experimentation platform or analytics foundations from scratch in a scale-up - MLOps tooling, feature stores, or real-time inference pipelines - Exposure to recommendation systems, NLP, or generative AI in a product context WHAT WE OFFER - Fully remote within the EU or Ukraine - B2B contract - 22 days of paid time off plus public holidays - Flexible working hours within core EU/Eastern European business hours - A rare chance to shape a data function from the ground up, with broad ownership and direct impact on the product roadmap