Senior Data Scientist, RC Capital

About RevenueCat

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, process $10B+ in annual purchase volume, and help developers worldwide understand and grow their revenue. We're a remote‑first company of 120+, spread across 25 countries, guided by values: Customer Obsession, Always Be Shipping, Own It, and Balance. If you want your work to touch hundreds of millions of end‑users and help developers get paid, you'll fit right in.

The Role: Senior Data Scientist, RC Capital

We're looking for a Data Scientist to support product initiatives for RevenueCat Capital, with deep experience in lead qualification, anomaly detection, fraud prevention, and underwriting. This is a chance to be the founding Data Scientist embedded within the Capital team, a greenfield opportunity to scale our new fintech business lines from <$1M to $100M+. You'll partner directly with leadership, collaborate across teams, and bring a new product to life inside RevenueCat. Your work will touch real money, real developers, and a product that is just getting started. Read more about the opportunity here.

The Opportunity: RC Capital

RevenueCat is on a mission to help developers make more money. We build software that helps apps implement and manage purchases, with over 50% of new subscription apps on the App Store launching with RevenueCat. OpenAI's mobile subscriptions run on RC. Top of funnel metrics are up 300%+ YoY.

RC Capital is our next chapter: we'll continue to help developers make more money, not just through software, but through financial products. Financial institutions would love to have what we already have:

• Trust + distribution: App developers already trust us in their purchase flow — the highest stakes moment in any user journey.
• Real-time, verifiable data: Cross-platform revenue plus leading indicators like installs, trials, conversions, and refunds.
• Unmatched industry insights: We know how apps earn money at scale, which improves underwriting and product design.

Our first product is Daily Payouts: a factoring product that lets developers get app store proceeds sooner. Scaling it is a big challenge, but it's just the beginning. There's so much more to build: credit cards, revenue-based lending, cohort-based financing. We've got a mountain to climb.

What You'll Do

• Own the Data Science strategy for RC Capital.
• Build the foundation for our underwriting and fraud detection systems from the ground up. You'll define the models, the signals, and the approach.
• Develop sophisticated models for lead qualification, anomaly detection, fraud prevention, and credit underwriting using real-time app revenue data.
• Partner closely with Product and Engineering to integrate risk signals and underwriting logic into customer-facing flows and internal decisioning engines.
• Analyze cross-platform revenue data to uncover insights that improve our underwriting models and product design.
• Build mechanisms for measuring impact, evaluating model performance, and driving prioritization of new data initiatives.
• Operate with high ownership in an ambiguous, fast-moving environment, helping to define the long-term vision for our financial products.

About You

You are a Senior Data Scientist who cares deeply about impact and has direct experience with models that carry real financial consequence.

Skills & Experience:

• 5+ years of data science experience, ideally with a strong background in fintech, credit, lending, or payments.
• Deep expertise in fraud and/or underwriting. You know how to build models that balance risk and growth, and you understand the nuances of financial data.
• Highly analytical and technical: expert in SQL and Python. You can build, deploy, and monitor models in production. You don't wait for someone else to pull the data.
• Understanding of mobile apps or developer ecosystems, or eagerness to learn this space and how apps earn money at scale.
• Act like an owner: Roll up your sleeves and get things done. Treat RevenueCat's balance sheet, product, and brand as your own.
• Thrive in ambiguity: Comfortable making low-information, high-stakes decisions. Quickly get to confidence, move on, and iterate.
• Systems thinker: See the process, look for opportunities to automate and build scalable solutions when the signal is strong enough.
• Know when it's good enough: Obsessed with getting things right, but aware of diminishing returns. Balance detail, speed, and ambition without losing sight of impact.

What Success Looks Like

In the first month:

• Understand how Daily Payouts works and the data powering it.
• Get to know the team and the current state of our underwriting and fraud approach.
• Form your own point of view on where the biggest gaps are.

Within the first 3 months:

• Have a baseline fraud detection model in production (imperfect is fine, measurable is required).
• Work with Product and Engineering to integrate risk signals into real customer flows.
• Define what "better" looks like for measurable improvement.

Within the first 6 months:

• Own the underwriting and fraud detection systems end to end.
• Influence the RC Capital product roadmap with data-backed proposals.
• Become the go-to expert on how RevenueCat's revenue data translates into financial risk signals.

Within the first 12 months:

• Lead new Data initiatives as the Capital product line expands beyond Daily Payouts.
• Help shape how Data Science operates within Capital as the team grows.
• Have a material impact on how RevenueCat deploys capital and manages risk at scale.

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.

Compensation Range: $208K