Data Scientist, FinEng

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 operate at the intersection of Product, Engineering, Risk, Finance, and Go-to-Market to ensure that paying for OpenAI products is seamless, reliable, scalable, and globally optimized. As OpenAI expands internationally and across product surfaces, FinEng plays a critical role in enabling durable, efficient revenue growth.

About the Role

As Manager of Data Science for Financial Engineering, you will lead the measurement, experimentation, and optimization strategy that powers OpenAI’s monetization infrastructure.

You will define how we measure and improve checkout, payments, subscriptions, and pricing systems globally—balancing conversion, risk, cost, reliability, and user experience. You will build and lead a high-leverage team responsible for establishing source-of-truth metrics, scaling experimentation, and driving executive-level revenue insights.

This role is both strategic and deeply technical: you’ll shape the long-term financial data architecture while guiding day-to-day experimentation that directly impacts revenue and international scale.

This role is based in San Francisco, CA. We use a hybrid model (3 days/week in office) and offer relocation support.

In this role, you will

Own the FinEng Measurement Strategy

• Define the north-star revenue and monetization metrics across checkout, payments, subscriptions, and pricing.

• Establish guardrails across conversion, fraud/risk, payment latency, cost-to-serve, and reliability.

• Partner with Finance to ensure alignment between product metrics and financial reporting.

Lead and Scale Experimentation

• Build and oversee the experimentation program for in-house checkout and subscription systems.

• Define staged rollouts, guardrails, and offline incrementality methods when online testing is constrained.

• Raise the bar on causal rigor across monetization decisions.

Build and Lead the FinEng DS Team

• Hire, mentor, and grow a team of high-impact data scientists.

• Set the technical direction for experimentation, causal inference, and monetization analytics.

• Create operating rhythms that translate insights into shipping decisions.

Drive Global Monetization Optimization

• Lead analytics for international payment method expansion, FX strategy, and pricing localization.

• Reduce involuntary churn through intelligent retry logic, targeted nudges, and payment optimization.

• Develop elasticity frameworks and pricing models that inform packaging and long-term revenue strategy.

Build Durable Data Infrastructure

• Partner with FinEng Data Engineering to create source-of-truth datasets and operational visibility.

• Establish SLIs/SLOs, alerting, and proactive monitoring across payment flows.

• Ensure analytics scales with product and geographic expansion.

• 7+ years in data science, experimentation, or product analytics, including leadership experience

• Experience leading monetization, payments, checkout, or subscription analytics

• Deep fluency in SQL and Python, and strong causal inference instincts

• A track record of building experimentation platforms or scaling testing programs

• Experience managing or mentoring high-performing data scientists

• Strong executive communication skills and ability to influence cross-functional leaders

You could be an especially strong fit if you have

• Payments infrastructure or PSP experience (bank rails, disputes, fraud/risk systems)

• Background in offline incrementality, uplift modeling, CUPED, or counterfactual evaluation

• Experience with global payment methods, FX strategy, and pricing optimization

• Built operational analytics systems (alerting, SLIs/SLOs, monitoring)

• Partnered closely with Finance or revenue accounting teams

This becomes one of the most leverage-heavy roles in the company because it directly impacts revenue durability, international expansion, and customer experience simultaneously.