Data Scientist, Financial Engineering
San Francisco • FullTime
Posted 11mo ago
About the job
As a Data Scientist on the Financial Engineering (FinEng) team, you will own the analytics and experimentation that drive improvements in our checkout, payments, subscriptions, and pricing & monetization systems. You will be responsible for defining key metrics, building reliable data assets, and designing experiments to boost conversion rates, reduce churn and payment failures, and expand global payment method coverage. Your work will have a direct impact on revenue, customer experience, and international scaling efforts.
Responsibilities
- Own checkout and payments analytics and experimentation across various methods and locales, focusing on improving conversion while managing risk and latency.
- Build and manage the experimentation program for in-house checkout, including defining success metrics, executing staged rollouts, and utilizing offline incrementality when online tests are not feasible.
- Create operational visibility and establish source-of-truth data with the FinEng Data Engineering team, delivering team-level metrics, SLAs, and self-serve dashboards.
- Lead subscription, retention, and monetization analytics, ensuring launch readiness for new subscription features, reducing involuntary churn through targeted interventions, and developing elasticity/FX frameworks for pricing optimization.
Requirements
- 5+ years of experience in a quantitative role (data science, product analytics, or experimentation) within high-growth or fintech environments.
- Fluency in SQL and Python, with a proven ability to design and interpret A/B tests and quasi-experiments.
- Experience in building product metrics from the ground up and operationalizing them for decision-making.
- Excellent communication skills to collaborate effectively with Product Managers, engineers, risk/finance partners, and executives.
- Demonstrated strategic thinking beyond statistical significance, with a clear understanding of tradeoffs between conversion, risk, cost, and user experience.
Benefits
- Hybrid work model (3 days in office per week)
- Relocation assistance for new employees