Requirements
- •5+ years of data science experience
- •Strong background in fintech, credit, lending, or payments
- •Deep expertise in fraud and/or underwriting
- •Expert in SQL and Python
- •Ability to build, deploy, and monitor models in production
- •Understanding or eagerness to learn mobile apps or developer ecosystems
- •Ability to act like an owner and take initiative
- •Comfortable making low-information, high-stakes decisions
- •Systems thinker with ability to automate and build scalable solutions
- •Ability to balance detail, speed, and ambition
What You'll Do
- •Own the Data Science strategy for RC Capital
- •Build the foundation for underwriting and fraud detection systems
- •Develop models for lead qualification, anomaly detection, fraud prevention, and credit underwriting
- •Partner with Product and Engineering to integrate risk signals and underwriting logic
- •Analyze cross-platform revenue data to improve underwriting models and product design
- •Build mechanisms for measuring impact and evaluating model performance
- •Operate with high ownership in an ambiguous, fast-moving environment
- •Lead new Data initiatives as the Capital product line expands
- •Help shape how Data Science operates within Capital as the team grows
Benefits
- •Competitive equity in a fast-growing, Series C startup
- •10-year window to exercise vested equity options
- •Fully remote and flexible work environment
- •4-5 weeks of suggested time off annually
- •$2,000 USD for workspace setup
- •$1,000 USD annual stipend for continuous learning
About RevenueCat
RevenueCat is a subscription management platform for apps that monetize through in-app purchases.
San Francisco, CA
50 - 100
Finance