Data Scientist, Financial Engineering
4 Hours ago • 5 Years + • $255,000 PA - $405,000 PA
Data Analysis
Job Description
OpenAI’s Financial Engineering (FinEng) team focuses on revenue flow, including pricing, checkout, payments, and subscriptions, collaborating with various departments to ensure seamless, reliable, and efficient financial operations globally. As a Data Scientist on FinEng, you will lead analytics and experimentation for checkout, payments, subscriptions, and pricing, defining key metrics, building data assets, and designing experiments to boost conversion, reduce churn, and expand global payment coverage, directly impacting revenue and customer experience.
Good To Have:
- Payments, checkout, or subscription analytics experience (PSPs, bank rails, disputes/refunds, risk, e-commerce).
- Background in offline incrementality methods, uplift modeling, CUPED/causal inference, or counterfactual evaluation.
- Experience with internationalization/local payments, FX, and pricing & packaging strategy.
- Comfort building operational analytics (alerting, SLIs/SLOs) and partnering closely with data engineering.
Must Have:
- Own checkout & payments analytics and experimentation across methods and locales.
- Build and run the experimentation program for in-house checkout.
- Create operational visibility and source-of-truth data with FinEng Data Engineering.
- Lead subscription, retention, and monetization analytics.
- 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.
- Strategic instincts beyond significance tests—clear thinking about tradeoffs.
Perks:
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts.
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit).
- 401(k) retirement plan with employer match.
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks).
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees.
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick and safe time (1 hour per 30 hours worked).
- Mental health and wellness support.
- Employer-paid basic life and disability coverage.
- Annual learning and development stipend to fuel your professional growth.
- Daily meals in our offices, and meal delivery credits as eligible.
- Relocation support for eligible employees.
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
About 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
- Strategic instincts beyond significance tests—clear thinking about tradeoffs (conversion vs. risk vs. cost vs. user experience)
You could be an especially great fit if you have
- Payments, checkout, or subscription analytics experience (PSPs, bank rails, disputes/refunds, risk, e-commerce)
- Background in offline incrementality methods, uplift modeling, CUPED/causal inference, or counterfactual evaluation
- Experience with internationalization/local payments, FX, and pricing & packaging strategy
- Comfort building operational analytics (alerting, SLIs/SLOs) and partnering closely with data engineering
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