Data Scientist, Cybersecurity

Details

OpenAI’s Agentic Data Science team helps shape how AI agents are built, deployed, and improved across its products. The team partners with product, engineering, research, and security teams to define meaningful measures of success, understand system behavior in the real world, and translate evidence into better decisions.

As AI agents gain the ability to write and execute code, access sensitive systems, and complete increasingly complex tasks autonomously, they create both opportunities and risks for cybersecurity. This role will help develop new ways to measure security, evaluate defenses, and distinguish genuine risk reduction from unnecessary user friction.

Responsibilities

• Define metrics and evaluation frameworks for AI-agent security, including security-control coverage, agent behavior, sensitive actions, access patterns, detection quality, and emerging risks.
• Quantify the effectiveness and operational costs of security safeguards, including false positives, blocked actions, escalations, approval delays, and recovery paths.
• Partner with engineering and data teams to improve instrumentation, connect fragmented telemetry, establish trusted datasets, and identify data-quality and coverage gaps.
• Identify signals of anomalous behavior, risky access, sensitive-data exposure, and other security-relevant activity.
• Evaluate whether security interventions improve detection quality, response times, and real-world security outcomes.
• Partner with product, engineering, and research teams to assess AI-powered cybersecurity products and their value in developer and enterprise workflows.
• Define quality measures for security findings, including accuracy, severity, actionability, duplication, resolution, and downstream impact.
• Connect model behavior and product changes to outcomes such as triage, remediation, and vulnerability reduction.
• Measure how users discover, investigate, validate, prioritize, and resolve security issues, and identify opportunities to improve activation, adoption, retention, and enterprise value.
• Design measurement and experimentation strategies using controlled experiments, staged rollouts, observational analyses, and other methods appropriate for high-stakes environments.
• Translate analysis into security and product strategy, clarify tradeoffs, recommend investments, and communicate findings to technical partners and senior leadership.
• Establish a security data science capability by creating a roadmap and durable operating rhythms across Data Science and Security.

Requirements

• 5+ years of experience in data science, applied research, analytics, or a related quantitative field, with a track record of owning ambiguous, high-impact problems.
• Experience in cybersecurity, trust and safety, fraud or abuse prevention, privacy, platform integrity, or another domain involving adversarial behavior and difficult-to-measure risks.
• Strong proficiency in SQL and Python, including experience investigating complex datasets, working with incomplete instrumentation, and building reproducible analytical workflows.
• Experience defining metrics and evaluation frameworks when ground truth is limited, outcomes are delayed, or important risks cannot be observed directly.
• Strong judgment in experimentation, causal inference, observational analysis, and the practical limitations of different measurement approaches.
• Ability to partner effectively with security engineers, product managers, software engineers, researchers, data engineers, and senior leaders.
• Ability to translate technical analysis into concrete improvements in products, systems, controls, or organizational priorities.
• Comfort working independently, defining a roadmap, and bringing structure to a domain without established processes or industry standards.

Additional Qualifications

• Experience with detection engineering, threat research, security operations, insider risk, identity and access management, or privacy-preserving security analytics.
• Familiarity with AI agents, large language models, model evaluations, automated code review, or AI-powered cybersecurity products.
• Experience evaluating security findings, vulnerability detection, remediation workflows, or developer-facing security tools.
• Experience balancing security effectiveness against user experience, including false positives, approval flows, operational burden, and recovery behavior.
• Experience building automated monitoring, anomaly detection, production-oriented data assets, or systems that connect model outputs to real-world outcomes.
• A track record of building cross-functional measurement programs or establishing analytical capabilities from the ground up.

Benefits

• Base pay range of $263,000–$515,000 per year, plus equity.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for health and dependent care expenses, as well as commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, company holidays, and paid office closures.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Office meals and eligible meal delivery credits.
• Relocation support for eligible employees.
• Additional benefits may include charitable donation matching and wellness stipends.

OpenAI is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities. Background checks are administered in accordance with applicable law.