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OpenAI’s Financial Engineering and Identity data science team owns how revenue flows through our products and builds the systems that enable people and organizations to access OpenAI products safely, seamlessly, and at global scale.
Identity sits at the critical intersection of growth, trust, and user experience. The team owns the experiences and infrastructure behind sign up, sign in, account recovery, authentication, and identity integrations across both consumer and enterprise products. As OpenAI expands across products and markets, Identity plays an increasingly important role in helping more users get started quickly while protecting them from abuse, fraud, and account compromise.
We're looking for the first dedicated Data Scientist to partner with the Identity organization. In this role, you will define how we measure success across the entire identity journey—from first-time sign up and onboarding through authentication, account recovery, and enterprise identity experiences. You'll develop the experimentation frameworks, metrics, and analytical approaches that guide product decisions while helping the team navigate one of Identity's core challenges: optimizing growth while maintaining trust and security.
You'll work closely with Product, Engineering, Design, Abuse, Risk, and Go-to-Market teams to identify opportunities, quantify trade-offs, and influence strategy. Some questions can be answered through A/B tests. Others require observational analyses, causal inference, and judgment under uncertainty.
This is an opportunity to shape the analytical foundations of a high-impact product area from the ground up.
This role is based in San Francisco, CA. We use a hybrid model (3 days/week in office) and offer relocation support.
Define the north-star metrics and measurement frameworks used to evaluate the identity experience across consumer and enterprise products.
Design and analyze experiments to optimize top-of-funnel performance, including sign up, sign in, onboarding, and account recovery experiences.
Partner with Identity Product and Engineering teams to improve activation, authentication success, and user experience while maintaining appropriate safeguards.
Quantify and communicate trade-offs between growth objectives and abuse prevention outcomes, including risks such as fraud and account takeover.
Develop methodologies to evaluate identity initiatives when randomized experimentation is not feasible, leveraging causal inference and observational analyses.
Establish reporting and executive-facing metrics that provide visibility into Identity health, funnel performance, and emerging opportunities.
Build source-of-truth datasets, dashboards, and analytical systems that enable scalable decision-making across the Identity organization.
Help shape the culture of data-informed decision-making as the first Data Scientist dedicated to Identity.
8+ years of experience in product data science, experimentation, product analytics
Experience owning product funnels and driving improvements through experimentation and measurement.
Strong expertise designing experiments and applying causal inference methods in production environments.
Experience partnering closely with Product and Engineering teams to solve ambiguous, cross-functional problems.
The ability to translate complex analytical findings into clear recommendations for both technical partners and senior leadership.
Advanced proficiency in SQL and Python.
A track record of independently defining metrics, building analytical frameworks, and influencing product strategy.
Experience working on identity, authentication, trust and safety, fraud, abuse prevention, growth, or other user-facing platform problems is a plus, but not required.
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