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.
We're in 50%+ of newly shipped subscription apps, we process $16B+ in annual purchase volume, and we help everyone from a solo developer to the OpenAI mobile team understand and grow their revenue.
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.
This isn't the right fit for everyone. The systems you’ll build here manage billions of dollars and touch hundreds of millions of end users, and we don’t take that lightly. You'll be expected to work hard and hold a high bar for what you ship, alongside some of the sharpest, most driven people you've worked with. If that sounds energizing rather than exhausting, keep reading.
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. We are looking for someone who actively looks at our data, understands our customers’ pain points, identifies opportunities, and pushes ideas forward.
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 we have not built yet.
You will be expected to bring ideas to the table, backed by analysis and clear hypotheses, and to influence product direction through data.
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.
This role has real ownership. You will not just support decisions, you will help drive them.
About you
You are a Senior Data Scientist who cares deeply about impact and product outcomes.
From a skills perspective, you bring:
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.
You recognize yourself in several of these:
You are highly proactive and opinionated, and you are comfortable pushing ideas forward.
You enjoy working with messy, real-world data and imperfect information.
You care more about creating customer value than academic elegance.
You are comfortable operating in ambiguity and building structure where none exists.
You enjoy working closely with Product teams and influencing decisions.
You are excited by the consumer subscription ecosystem and curious about how developers make money.
What success looks like
In the first month, you'll:
Understand our data models.
Get to know the team.
Ramp up on the ongoing data feature work.
Implement and ship your first project.
Within the first 3 months, you'll:
Meaningfully contribute to shipping a data feature to thousands of developers.
Learn the basics of incident response, and be part of the on-call rotation.
Work with our Product, Analytics and Engineering teams to improve our data pipelines for data science features.
Launch your own explorations into our data to fulfill your own curiosity.
Within the first 6 months, you'll:
Own one or more core data-powered features end to end.
Influence the data feature roadmap with clear, data-backed proposals.
Be a go-to partner for product teams on data-driven decision making.
Within the first 12 months, you'll:
Propose and lead entirely new data-driven product initiatives.
Push the boundaries of how RevenueCat uses data to help developers grow revenue.
Help shape how data science operates at RevenueCat as the function grows.
What we offer:
Competitive equity in a fast-growing, Series C startup backed by top-tier investors, including Y Combinator
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
Interviewing at RevenueCat
Our interview process is rigorous on purpose. We want to be sure that everyone we bring on is genuinely excited about this work, aligned with how we operate, and ready to meet our high bar for performance. Curious what that actually looks like? Read more in our blog post on how we hire at RevenueCat, including tips to help you succeed.
More on how we work:
How we think about hiring and team design: Building a Winning Team
The values that guide how we work: Our Values
How we work as a remote team: How We Work Remotely at RevenueCat
What to expect from our interview process: Interview Expectations
What to expect from comp and employment: Employment FAQ