Quantitative Risk Intelligence Analyst

OpenAI; United States; Hybrid; USD 198,000 - 320,000; Full time

Benefits offered by this job

Relocation support

Daily meals in offices

Annual learning & development stipend

Paid parental leave

Paid time off & holidays

Wellness & mental health programs

Job summary

OpenAI is seeking a Quantitative Intelligence Analyst to rapidly identify emerging risks in complex human–AI systems. You will use quantitative tooling to surface weak signals, build models, and translate risks into measurable indicators for detection and mitigation.

This hybrid role includes relocation support and a path to impact safety decisions at scale. You will leverage Python and SQL to mine data, develop stress tests, and inform strategic risk products across teams.

Qualifications

• 3+ years of experience in quantitative intelligence analysis or risk-focused research.
• Experience with data mining, statistical modeling, and supervised learning.
• Ability to translate trust and safety challenges into measurable signals.
• Experience in monitoring signals for data drift and performance degradation.

Responsibilities

• Discover and define new quantitative risk signals where metrics do not yet exist.
• Translate complex trust challenges into measurable signals for tracking.
• Develop upstream signal frameworks to inform detection and mitigation.
• Analyze risk trends and identify drivers behind changes.
• Conduct data mining and modeling to understand risk evolution across systems.
• Design adversarial scenarios and stress tests to evaluate exposure and gaps.
• Produce clear, data-driven briefs to support risk prioritization.

Skills

Quantitative analysis

Risk analysis

Trust & safety

Data mining

Statistical modeling

Supervised learning

Tools

Python

SQL

Agent-based modeling

Monte Carlo simulations

Red team exercises

Job description

OpenAI is seeking a Quantitative Intelligence Analyst to rapidly identify emerging risks in complex human–AI systems. You will use quantitative tooling to surface weak signals, build models, and translate risks into measurable indicators for detection and mitigation.

This hybrid role includes relocation support and a path to impact safety decisions at scale. You will leverage Python and SQL to mine data, develop stress tests, and inform strategic risk products across teams.