Data Scientist
Hover or tap a row for full statistics (EUR / month on this chart).
Salary analysis
Compared with the selected benchmark ("All roles in Stockholm, Sweden"), this listing's salary midpoint is about 94% lower. The offer sits below the benchmark range (€3,904–€12,918). The listed pay band (€463–€600) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 13 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| Market Average: Data Scientist | €3,180/per month | €5,775/per month | €8,713/per month |
| All roles in Stockholm, Sweden | €3,904/per month | €7,051/per month | €12,918/per month |
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. 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 the team trusts trustworthy: quality, definitions, and lineage. OUR TECH STACK We\'re building with tools that both humans and AI love: - Languages: SQL and Python - Warehouse & events: BigQuery, PubSub - Analytics & product: Hex, Lovable Apps - Experimentation: A/B and growth testing - Cloud: GCP
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