Description
Job Posting
Data Scientist, Preparedness
Location
San Francisco
Employment Type
Full time
Department
Data Science
Compensation
- $347K – $400K • Offers Equity
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
More details about our benefits are available to candidates during the hiring process.
This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.
About the Team
The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework.
Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models.
The mission of the Preparedness team is to:
- Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society
- Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems
Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society.
About the Role
We’re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes.
This position goes beyond “running evals.” You’ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm).
What You’ll Do
- Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas).
- Diagnose false positives and false negatives with deep error analysis, root cause investigation, and clear recommendations for mitigation adjustments.
- Build monitoring and measurement frameworks to track mitigation effectiveness over time and across user segments and use cases.
- Identify trends in over-blocking vs. under-blocking, quantify customer impact, and propose prioritized interventions.
- Develop insights from customer feedback, complaints, and usage patterns to detect shifts in adversarial behavior and system failure modes.
- Expand risk monitoring into new areas, including cybersecurity threats and model loss-of-control or sabotage scenarios, in partnership with domain experts.
- Communicate results to technical and executive stakeholders with crisp narratives, decision-ready metrics, and clear tradeoffs.
You might thrive in this role if you are:
- An autonomous operator: you can take a problem statement and independently structure the analysis end-to-end.
- Strong at executive-ready communication: concise, clear, and outcome-oriented.
- Skilled in turning analysis into productable changes: you’re comfortable influencing across functions to drive mitigation improvements.
Qualifications
- Significant experience in data science or applied analytics in high-stakes domains (e.g., security, trust & safety, abuse prevention, fraud, platform integrity, or reliability).
- Strong foundations in experimentation, causal thinking, and/or observational inference; ability to design robust measurement under imperfect data.
- Fluency in SQL and Python (or equivalent) for analysis, modeling, and building monitoring workflows.
- Experience building metrics, dashboards, and operational monitoring that meaningfully changes outcomes (not just reporting).
- Track record of driving cross-functional impact with engineering, product, and research partners