Senior Data Scientist, Product - RevenueCat

RevenueCat gives app businesses the infrastructure and tools to build, run, and improve their monetization. Since graduating from YC's S18 batch, we've grown into the default monetization platform for mobile, processing $16B+ in annual purchase volume.

We're a remote-first team of 150+ people across 25+ countries, guided by values we actually practice: Customer Obsession, Always Be Shipping, Own It, and Balance.

The Role

We are looking for a Senior Product Data Scientist who is deeply product-minded and highly proactive. This is not a role for someone who waits for perfectly defined questions or works in isolation.

You will work closely with Product, Engineering, and Analytics to shape what we build, why we build it, and how we measure success. Your work will directly power customer-facing features such as LTV prediction, experimentation and statistical significance, benchmarking, and entirely new data-driven products.

Our data stack includes a Python backend, PostgreSQL production databases, Snowflake, dbt, and AWS.

What You Will Do

• Proactively explore RevenueCat’s data to identify customer problems, opportunities, and product bets.
• Translate ambiguous product and business problems and questions into clear analyses, models, and recommendations.
• Partner with Product Managers to shape roadmaps, not just execute on them.
• Design, build, and ship production-grade predictive and descriptive models that power customer-facing features.
• Define and evaluate statistical approaches for experimentation, benchmarking, and forecasting.
• Communicate insights clearly and persuasively to technical and non-technical audiences, with a focus on customer impact.
• Continuously iterate on shipped models and features based on real-world usage and feedback.

About You

• 5+ years of experience working as a Data Scientist.
• Strong SQL skills and comfort with data modeling.
• Experience building and deploying predictive and descriptive models in production.
• Experience writing or collaborating on production-ready Python code.
• A solid understanding of statistics and experimentation, ideally including Bayesian approaches.
• The ability to clearly explain complex ideas and results to broad audiences.

What We Offer

• Competitive equity in a fast-growing, Series C startup backed by top-tier investors
• 10-year window to exercise vested equity options
• A fully remote environment designed around autonomy and flexibility
• 4-5 weeks of flexible time off annually
• Paid desk at a co-working space
• Workspace budget and continuous learning stipend