[Hiring] Senior Data Scientist @RevenueCat

Role Description

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
• 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:

• Python backend
• PostgreSQL production databases
• Snowflake
• dbt
• AWS

Qualifications

• 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

Requirements

• 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

Benefits

• 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

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