About the job
About Our Team
At OpenAI, our mission is to ensure that artificial intelligence benefits all of humanity. The ChatGPT for Work initiative is a crucial part of this mission, as it empowers individuals to harness the full potential of AI in their daily tasks. By minimizing time spent on repetitive duties and coordination, we enable our users to focus on meaningful and impactful work. We are developing an AI-driven workspace where AI serves as a super-assistant for routine tasks and as a collaborative partner that users can delegate work to, review, edit, and approve with confidence.
Our approach ensures that organizations can trust our solutions, as we ground our experiences in the appropriate company context and systems, providing safety and reliability.
Role Overview
As a Data Scientist for ChatGPT for Work, you will play a pivotal role in shaping our product strategy through data insights. Your responsibilities will include identifying the most pressing user problems, developing sharp hypotheses to enhance team and business outcomes, and influencing future developments by presenting compelling, evidence-based recommendations. You will be the Directly Responsible Individual (DRI) for the insight → strategy → experiment → decision loop, defining success metrics for teams, identifying critical adoption and retention barriers, and translating signals into actionable product direction.
Collaboration will be key, as you will work closely with Product, Engineering, Research, and Finance teams to ensure our metrics are reliable, our experimentation is thorough, and our insights lead to tangible product improvements.
This position is based in San Francisco, utilizing a hybrid work model that requires three days in the office each week. We also offer relocation assistance to new employees.
Key Responsibilities:
Develop and own the core KPI framework for ChatGPT for Work, covering onboarding, activation, engagement, retention, and expansion, along with quality and trust metrics.
Create end-to-end funnels to analyze where individuals and teams excel or encounter challenges, from initial workspace setup to sustained usage and long-term value creation.
Define and operationalize metrics related to “time-to-value” and collaboration loops, linking them to significant business outcomes.
Design and assess experiments and rollouts to measure the impact of product modifications across key workflows.
Collaborate with product and engineering teams to enhance data instrumentation, quality, and metric definitions, ensuring rapid and accurate decision-making.
Translate complex analyses into clear and persuasive insights that will help shape our product strategy and roadmap.

