Data Scientist, API

About the Team OpenAI’s mission is to ensure AGI benefits all of humanity. The API organization is one of the highest-leverage ways we do that: we put frontier intelligence in the hands of builders who turn it into products, businesses, and services that reach people everywhere. We build the infrastructure and developer platform that makes that possible—so developers can reliably bring powerful AI into the real world, operate it safely at scale, and keep pushing what’s possible. When we do our job well, we don’t just ship an API. We enable thousands of teams to create new capabilities for millions of end users, accelerating progress across industries and communities. About the Role As a Data Scientist on the API team, you’ll build the measurement systems that make our platform legible and improveable. You’ll define the metrics that matter, identify and quantify developer friction, evaluate launches and platform changes, and translate data into product decisions that improve reliability and developer outcomes at scale. You’ll partner closely with Product, Engineering, Research, and Finance to ensure our metrics are trusted, our experimentation is rigorous, and our insights turn into shipped improvements. This role is based in San Francisco. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Own the core KPI framework for the API platform, spanning developer adoption, engagement, retention, and platform health. Build end-to-end funnels that identify where developers succeed or get stuck—from first integration through scaling to production. Define and operationalize platform guardrails (e.g., reliability, latency, error rates, cost/efficiency) and connect them to user outcomes. Design and evaluate experiments and rollouts to quantify the impact of platform and product changes. Partner with product and engineering teams to improve instrumentation, data quality, and metric definitions so decisions are fast and correct. Translate complex analysis into clear, actionable insights for leadership and cross-functional stakeholders. Develop and socialize dashboards, tools, and self-serve data products that help teams answer product questions quickly. Help establish data science standards and best practices for measuring AI platform performance and developer success. Partner with other data scientists across the company to share learnings and raise the bar on measurement and decision-making. You might thrive in this role if you have: 10+ years of experience in data science roles within product or technology organizations (platform or developer-facing experience is a plus). Expertise in statistics and causal inference, applied in both experimentation and observational studies. Expert-level SQL and proficiency in Python for analytics, modeling, and experimentation. Proven experience designing and interpreting experiments and making statistically sound recommendations. Experience building datasets, metrics, and data pipelines that power production decision-making. Experience developing and extracting insights from business intelligence tools (e.g., Tableau) and building self-serve solutions. Strong product sense and an impact-driven mindset: you turn ambiguity into crisp frameworks that drive roadmap decisions. Ability to build relationships with diverse stakeholders and cultivate strong partnerships across Product, Engineering, Research, and GTM teams. Strong communication skills, including the ability to bridge technical and non-technical audiences. Ability to operate effectively in a fast-moving, ambiguous environment with limited structure. Are consistently among the first to adopt the latest AI tools, you use them daily to increase your own throughput, and you proactively turn them into durable workflows that change how your team and org operate. Nice-to-haves: Experience with developer platforms, APIs/SDKs, or usage-based products. Experience with platform reliability analytics, incident impact measurement, or performance/cost optimization. Familiarity with AI evaluation and quality measurement systems (online/offline evals, human-in-the-loop, safety/quality guardrails). Why it matters When developers build on OpenAI, they put our platform into products that touch millions of people. API Data Science ensures we make the right bets, operate with rigor, and continuously raise reliability and usability as the platform scales. This is a unique opportunity to shape how frontier AI is measured, improved, and delivered through a platform that powers the next generation of AI products. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs a