About the job
About the Team
At OpenAI, our mission is to ensure that artificial general intelligence (AGI) positively impacts all of humanity. The API team is crucial to this mission, empowering innovators to harness cutting-edge intelligence and transform it into impactful products, businesses, and services for people around the globe.
We are dedicated to constructing the infrastructure and developer platform that facilitates this process. Our goal is to enable developers to seamlessly integrate robust AI into real-world applications, operate it safely at scale, and continuously explore new possibilities. By excelling in our roles, we don’t merely launch an API; we empower numerous teams to deliver novel capabilities to millions of users, driving innovation across various industries and communities.
About the Role
As a Data Scientist within the API team, you will be instrumental in developing measurement systems that enhance the clarity and continuous improvement of our platform. Your responsibilities will include defining essential metrics, identifying and quantifying developer challenges, evaluating product launches and platform modifications, and converting data insights into actionable product decisions that enhance reliability and developer experiences at scale.
You will closely collaborate with the Product, Engineering, Research, and Finance teams to ensure our metrics are reliable, our experimentation is thorough, and our insights lead to effective improvements.
This position is based in San Francisco, and we operate on a hybrid model, requiring three days in the office each week, with relocation assistance available for new hires.
Key Responsibilities:
Lead the development of the core KPI framework for the API platform, focusing on developer adoption, engagement, retention, and platform health.
Create comprehensive funnels to identify success and obstacles faced by developers, from initial integration to production scale.
Establish and operationalize platform guardrails (e.g., reliability, latency, error rates, cost-effectiveness) and correlate them with user outcomes.
Design and assess experiments and rollouts to measure the effects of platform and product enhancements.
Collaborate with product and engineering teams to enhance instrumentation, data quality, and metric definitions, ensuring rapid and accurate decision-making.
Translate complex analytical findings into clear, actionable insights for leadership and cross-functional teams.
Develop and share dashboards, tools, and self-service data products that enable teams to quickly address product inquiries.
Contribute to the establishment of data science standards and best practices within the organization.

