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Data Scientist, Safety

OpenAI

Data Scientist, Safety is a still-open role at OpenAI on Jobrow. Location: Hybrid · San Francisco · California · United States. Listed pay: $265k–$380k. Sourced from the company's public Ashby board. First seen 2 months ago; last confirmed 9 days ago. Apply on the employer ATS — Jobrow is not the employer.

Pay
$265k–$380k
Workplace
Hybrid
Location
San Francisco · California · United States
First seen
2 months ago
Last seen
9 days ago
Board
Ashby
Apply

About this role

ABOUT THE TEAM OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally.

  • Seniority: mid
  • python
  • sql

Location & pay

Hybrid · San Francisco · California · United States Listed pay on Jobrow: $265k–$380k.

Source

Jobrow reads the public Ashby board for OpenAI. First seen 2 months ago; last seen 9 days ago. We are not the employer — apply only on the company ATS.

Posting

ABOUT THE TEAM OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company’s most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. We are hiring Data Scientists across several teams that contribute to safety in different ways, including: - Safety Systems - Integrity - Product Policy This is a high-impact role operating at the intersection of product, safety, policy, and research.   About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: - Measure harmful or abusive behavior across OpenAI’s products - Detect fraud, manipulation, coordinated misuse - Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows - Design experiments and causal analyses to understand product, policy, and mitigation impacts - Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks - Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs - Translate ambiguous safety risks into measurable problems and evidence-based recommendations - Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes - Build zero-to-one analytical systems in rapidly evolving domains   Ideal Candidate We’re looking for strong Data Scientists who thrive in ambiguous, high-leverage environments. You may be a fit if you have: - Strong statistical reasoning and analytical judgment - Experience with experimentation, causal inference, or observational analysis - Strong SQL and Python skills - Experience working with messy, incomplete, or noisy datasets - Ability to structure open-ended business or risk problems - Excellent communication with technical and non-technical stakeholders - High ownership and comfort operating independently Helpful backgrounds include: - Trust & Safety / Integrity - Fraud & abuse - Security analytics - AI/ML model mea

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