Strategic Quantitative Risk Analyst

OpenAI; San Francisco (CA); Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Relocation support

Hybrid work schedule

Job summary

OpenAI is seeking a Quantitative Intelligence Analyst to identify emerging risks in complex human–AI systems before they are well-defined. You will leverage deep subject matter expertise and quantitative tooling to surface early risk signals and translate ambiguous patterns into data-driven insights, informing mitigation and strategic planning.

Based in San Francisco with a hybrid schedule (3 days/week) and relocation support, you will build analytic models, stress-test scenarios, and socialize

Qualifications

• 3+ years of experience in quantitative intelligence analysis, trust & safety, security analysis, or risk-focused research.
• Comfortable with complex trust & safety domains such as child safety, violent activities, self-harm, or similar high-stakes risk areas.
• Familiarity with data mining, statistical modeling, and supervised learning methods.
• Understand how to monitor signals or models for data drift, behavioral adaptation, or performance degradation over time, and diagnose likely causes.
• Experience in operationalizing adversarial or strategic risk behaviors, including through red-team exercises, agent-based modeling, or structured scenario analyses.
• Comfortable working with Python and SQL.
• Nice to have: Experience with quantitative stress testing or Monte Carlo simulations to assess uncertainty and tail risk.

Responsibilities

• Discover and define new quantitative risk signals where no established metrics exist, using subject matter expertise to surface early, weak, or unconventional indicators.
• Translate complex trust and safety challenges into measurable signals that can be tracked and stress-tested over time.
• Develop upstream early-warning and signal frameworks that inform downstream detection and mitigation efforts.
• Analyze risk trends to assess the underlying drivers and causal factors behind those changes.
• Conduct data mining and statistical modeling to understand how risks originate, evolve, and propagate across systems.
• Design adversarial scenarios, and quantitative stress tests to assess exposure, coverage gaps, and vulnerabilities.
• Produce clear data-driven briefs to support risk prioritization, contingency planning, and strategic risk products across teams.

Skills

Python

SQL

Data mining

Statistical modeling

Trust & safety

Risk analysis

Adversarial / red-team

Agent-based modeling

Structured scenario analyses

Supervised learning

Job description

OpenAI is seeking a Quantitative Intelligence Analyst to identify emerging risks in complex human–AI systems before they are well-defined. You will leverage deep subject matter expertise and quantitative tooling to surface early risk signals and translate ambiguous patterns into data-driven insights, informing mitigation and strategic planning.

Based in San Francisco with a hybrid schedule (3 days/week) and relocation support, you will build analytic models, stress-test scenarios, and socialize