Data Scientist, Financial Engineering
OpenAIAbout the Team
OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide.
About the Role
As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments, subscriptions, and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally.
This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
In this role, you will
Own checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency.
Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible.
Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action.
Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality.
You might thrive in this role if you have
5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments
Fluency in SQL and Python, with a track record designing and interpreting A/B tests and quasi-experiments
Experience building product metrics from scratch and operationalizing them for decision-making
Excellent communication skills with PMs, engineers, risk/finance partners, and executives