At a Glance
- Tasks: Explore data to identify customer problems and drive product decisions.
- Company: Join a remote-first startup revolutionising in-app subscriptions.
- Benefits: Competitive equity, flexible work, generous time off, and learning stipends.
- Other info: Be part of a dynamic team influencing the future of data science.
- Why this job: Make a real impact on developers' revenue and shape innovative products.
- Qualifications: 5+ years as a Data Scientist with strong SQL and Python skills.
The predicted salary is between 70000 - 90000 £ per year.
RevenueCat removes the headaches of building and scaling in-app subscriptions. Since graduating from YC's S18 batch we've grown into the default monetization platform for mobile: we're in > 40% of newly shipped subscription apps, we process $12B+ in annual purchase volume, and we help everyone from a solo dev in Brazil to the OpenAI mobile team understand and grow their revenue.
We're a remote-first crew of 150+, spread across 25+ countries, and guided by values we actually practice: Customer Obsession, Always Be Shipping, Own It, and Balance. If you want your work to touch hundreds of millions of end-users (and help the developers behind them get paid), you'll fit right in.
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.
- 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 fulfil 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.
- Fully remote and flexible work environment.
- 4-5 weeks of suggested time off annually for mental, physical, and emotional recharge.
- $2,000 USD for workspace setup and $1,000 USD annual stipend for continuous learning.
Curious about the interview process? Discover more in our blog post about how we hire and learn tips to help you succeed.
Senior Product Data Scientist employer: RevenueCat
RevenueCat is an exceptional employer for those seeking to make a significant impact in the app economy. With a fully remote and flexible work environment, employees enjoy a strong work-life balance, competitive equity options, and generous time off to recharge. The collaborative culture fosters growth and innovation, allowing team members to shape the company's narrative and voice while working alongside passionate colleagues from diverse backgrounds across the globe.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Product Data Scientist
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like RevenueCat!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Product Data Scientist at RevenueCat.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like RevenueCat.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Product Data Scientist at RevenueCat, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Product Data Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at RevenueCat, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at RevenueCat. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at RevenueCat
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at RevenueCat!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.