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Mid LevelFull-timePythonRustAWSData ScienceAIData
Salary Range
$80,750 - $109,250 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
The Preparedness team at OpenAI is seeking a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role requires an experienced, highly autonomous individual who can structure rigorous analyses and translate findings into actionable product and policy changes. The position involves creating mitigation intelligence and monitoring systems to detect issues early, measure effectiveness over time, and reduce both over-blocking and under-blocking.
Key Responsibilities
- →Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains like 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.
Requirements
- ✓Significant experience in data science or applied analytics in high-stakes domains such as 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.
- ✓Cybersecurity data science experience (strong preference), including exposure to threat modeling, adversarial dynamics, abuse patterns, or security telemetry.
- ✓Experience with classifier evaluation, calibration, thresholding, and error analysis at scale. Familiarity with detection systems in adversarial settings (e.g., evasion, distribution shift, feedback loops).
- ✓Trust & Safety experience is helpful, but not required.
- ✓Genuine interest in AI safety, alignment, and catastrophic risk prevention.
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