[Hiring] Senior Data Scientist @RevenueCat

Role Description

We're looking for a Data Scientist to support product initiatives for RevenueCat Capital , with deep experience in:

• Lead qualification
• Anomaly detection
• Fraud prevention
• 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.

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.
• Develop sophisticated models for lead qualification, anomaly detection, fraud prevention, and credit underwriting.
• 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.

Qualifications

• 5+ years of data science experience, ideally with a strong background in fintech, credit, lending, or payments.
• Deep expertise in fraud and/or underwriting.
• Ability to build models that balance risk and growth, with an understanding of the nuances of financial data.
• Highly analytical and technical.
• Expert in SQL and Python, capable of building, deploying, and monitoring models in production.
• Understanding of mobile apps or developer ecosystems, or eagerness to learn this space.
• Ownership mentality, treating RevenueCat's balance sheet, product, and brand as your own.
• Comfortable making low-information, high-stakes decisions.
• Systems thinker, looking for opportunities to automate and build scalable solutions.
• Ability to balance detail, speed, and ambition without losing sight of impact.

What success looks like

In 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.
• Work with Product and Engineering to integrate risk signals into real customer flows.
• Define what "better" looks like for improvement.

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.
• 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.
• 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.

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.
• 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.