Quantitative Intelligence 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

About the Team

The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity.

The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors.

About the Role

As a Quantitative Intelligence Analyst, you will focus on discovering novel and emerging risks in complex human–AI systems before they are well-defined, measurable, or widely understood.

You will use deep subject matter expertise and quantitative tooling to surface weak, early, and unconventional risk signals. You will build analytic models that explain how harms could emerge and translate ambiguous patterns into structured, data-driven insight. Your work will help identify potential gaps in policy or coverage and operationalize previously unmeasured problems into signals that can support detection, mitigation, and planning downstream. You will develop analytical frameworks that map how new risks form, evolve, and propagate as products change, policies shift, and external events unfold. Your analyses will directly inform strategic risk prioritization and planning across the company, with regular visibility through strategic risk products.

This role is based in office (hybrid, 3 days/week). Relocation support is available

In this role, you will:

• 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

You might thrive in this role if you:

• Have 3+ years of experience in quantitative intelligence analysis, trust & safety, security analysis, or risk-focused research
• Are comfortable working on complex trust and 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 can 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

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

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