Data Scientist, Preparedness

Highlights

• Build mitigation intelligence to prevent extreme harms from frontier AI systems.
• Evaluate detection pipelines across biosecurity, cybersecurity, and emerging risks.
• Track mitigation effectiveness over time and expand monitoring to new risk areas.

What they offer

• Equity

Ideal candidate

Autonomous, impact-driven data scientist with background in high-stakes security or integrity domains who cares deeply about preventing catastrophic AI risks and turning analysis into real product safeguards.

Requirements

• Significant experience in data science or applied analytics in high-stakes domains
• Strong foundations in experimentation, causal thinking, and observational inference
• Fluency in SQL and Python for analysis, modeling, and monitoring workflows
• Experience building metrics, dashboards, and operational monitoring
• Track record of driving cross-functional impact with engineering, product, and research
• Cybersecurity data science experience with threat modeling and adversarial dynamics
• Experience with classifier evaluation, calibration, thresholding, and error analysis