Data Scientist, Strategic Intelligence & Risk

The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity.

The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors.

About the Role

As a Data Scientist, you will lead econometric and experimental analysis to understand how risk changes in complex human–AI systems. Your work will focus on measuring the magnitude and impact of risk shifts in a fast-paced, rapidly evolving operational environment. You will design experiments and observational studies to identify causal drivers and analyze changes in risk across a wide range of surfaces and sources. Your analyses will directly inform prioritization and strategic risk management across the company.

This role is based in San Francisco, CA (hybrid, 3 days/week). Relocation support is available

In this role, you will:

• Own the design and execution of experimental and observational analyses used to assess strategic risk

• Develop econometric approaches to estimate the impact of product, policy, and external developments on key risk vectors

• Translate strategic risk questions into testable hypotheses and sound study designs

• Design and deploy A/B tests, as well as pseudo-experimental studies, to measure changes in risks and understand underlying mechanisms

• Identify, test, and explain product-driven, event-driven, or signal-driven changes in risk

• Establish baselines and statistical confidence around core metrics to size these problems

• Partner across teams to track strategic risks, identify opportunities for intervention, and develop analyses to evaluate those interventions

• Have 3–6+ years in econometrics, causal inference, or experimental research

• Are comfortable owning ambiguous analyses with large-scale influence

• Are strong in experimental design, observational methods, and statistical reasoning

• Write solid Python and SQL

• Experience delivering zero-to-one analyses and scaling them from concept through deployment

• Communicate data-driven findings clearly, including uncertainty and trade-offs, to non-technical partners and leadership

• Nice to have: experience in trust and safety, integrity, operational security, intelligence analysis or other quantitative risk-focused domains