Data Scientist, Identity
First Data Scientist for OpenAI's Identity team. Define metrics, run experiments, and build analytical systems to optimize sign-up, authentication, and account recovery while balancing growth and trust.
About the job
Responsibilities
- 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.
Requirements
- 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.
Nice-to-Haves
- Experience working on identity, authentication, trust and safety, fraud, abuse prevention, growth, or other user-facing platform problems.
Skills
SQL, Python, Experimentation, Causal Inference, Product Analytics, A/B Testing, Data Visualization, Dashboarding, Metrics Definition, Funnel Analysis
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