About the role
TL;DR - You own the metrics for a product area, find where users get stuck or drop off, and turn that into product bets that ship. You build the measurement and experimentation the teams rely on, and the systems that surface opportunities without waiting on you. Why Lovable? Lovable lets anyone and everyone build software with any language. From solopreneurs to Fortune 100 teams, millions of people use Lovable to transform raw ideas into real products, fast. We are at the forefront of a foundational shift in software creation, which means you have an unprecedented opportunity to change the way the digital world works. Lovable-built applications and websites are visited hundreds of millions of times a month, and our enterprise footprint is compounding fast. And we're just getting started. We're a small, talent-dense team building a generation-defining company from Stockholm. We value extreme ownership, high velocity, and low-ego collaboration. We seek out people who care deeply, ship fast, and are eager to make a dent in the world.
What we're looking for A product-minded data scientist who owns a product area's outcomes: you find the opportunity, form the bet, and see it shipped, rather than handing insights to a PM. You build systems, not one-offs: the instrumentation, metrics, and agents that produce insight and flag opportunities proactively. Strong SQL, Python, applied statistics, and experimentation (A/B and growth tests). Deep instinct for user behavior: activation, engagement, retention, and what moves them. Comfortable shipping directional answers fast, and knowing when a decision needs rigor. Entrepreneurial. Thrives with autonomy and ambiguity, and works shoulder to shoulder with product and engineering.
What you'll do Own the metrics and funnels for a product area, and drive measurable improvement in activation, engagement, and retention. Find opportunities in user behavior and turn them into product bets, working directly with PMs and engineers to ship them. Design and run experiments, and act on the results. Build the instrumentation, semantic models, and agents the product team runs on. Keep the data