Original listing text, shown exactly as published by the company.
The Role
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 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 CapitalRevenueCat 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. Nothing is locked in, you'll define the models, the signals, and the approach.
- Develop sophisticated models for lead qualification, anomaly detection, fraud prevention, and credit underwriting. All this using the richest, most real-time app revenue data in the world.
- 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 youYou are a Senior Data Scientist who cares deeply about impact and has direct experience with the kind of models that carry real financial consequence. From a skills perspective, you bring:
- You have 5+ years of data science experience, ideally with a strong background in fintech, credit, lending, or payments.
- You have 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.
- You're highly analytical and technical. You are an 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.
- You understand mobile apps or developer ecosystems, or you're eager to learn this space and how apps earn money at scale.
- You act like an owner. You aren't afraid to roll up your sleeves and get something done yourself. You treat RevenueCat's balance sheet, product, and brand like it's your own.
- You thrive in ambiguity. You are comfortable making low-information, high-stakes decisions. You can quickly get to confidence, move on, and iterate.
- You're a systems thinker. You can step back from the particular and see the process. You look for opportunities to automate and build things that scale, when you've had enough signal to know that you should.
- You know when it's good enough. You are obsessed with getting things right, but you know when you're at diminishing returns. You balance detail, speed, and ambition without losing sight of impact.
What success look likeIn the first month, you'll
- Understand how Daily Payouts works today and what data powers 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, you'll
- 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 so we have something to improve against.
Within the first 6 months, you'll
- Own the underwriting and fraud detection systems end to end.
- Influence the RC Capital product roadmap with data-backed proposals on what to build next.
- Be the person who knows best how RevenueCat's revenue data translates into financial risk signals.
Within the first 12 months, you'll
- 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 had a material impact on how RevenueCat deploys capital and manages risk at scale.
