Data Scientist, Preparedness
San Francisco • FullTime
Posted 6mo ago
About the job
OpenAI is seeking a Data Scientist to join the Preparedness team, a critical part of the Safety Systems organization. This role focuses on building, evaluating, and improving mitigations to prevent extreme harms from AI systems. You will go beyond standard evaluations to create intelligence and monitoring systems that enable early issue detection, measure mitigation effectiveness, and reduce both over-blocking and under-blocking of harmful content. This is a fast-paced, impactful role for an experienced, autonomous individual contributor who can structure rigorous analyses and translate findings into actionable product and policy changes.
Responsibilities
- Evaluate and improve mitigation systems, including classifiers and detection pipelines across various domains.
- Diagnose false positives and false negatives through deep error analysis and root cause investigation.
- Build monitoring and measurement frameworks to track mitigation effectiveness over time and across different 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, such as cybersecurity threats and model loss-of-control scenarios.
- Communicate results to technical and executive stakeholders with clear narratives and decision-ready metrics.
Requirements
- Significant experience in data science or applied analytics in high-stakes domains like security, trust & safety, or fraud.
- Strong foundations in experimentation, causal thinking, and/or observational inference.
- Fluency in SQL and Python for analysis, modeling, and building monitoring workflows.
- Experience building metrics, dashboards, and operational monitoring that drive outcomes.
- Track record of driving cross-functional impact with engineering, product, and research partners.
- Cybersecurity data science experience is strongly preferred, including exposure to threat modeling or adversarial dynamics.
- Experience with classifier evaluation, calibration, thresholding, and error analysis at scale.
- Familiarity with detection systems in adversarial settings.
- Genuine interest in AI safety, alignment, and catastrophic risk prevention.