Data Science Manager, Integrity

Details

About the Team

Integrity Data Science sits at the center of OpenAI's mission to deploy powerful AI responsibly. The team builds measurement systems, experimentation practices, and detection/mitigation strategies that protect OpenAI and its users from misuse, fraud, and adversarial behaviors. As Integrity work expands across product surfaces and go-to-market motion, this role will scale the team, strengthen execution across multiple Integrity domains, and deepen partnership with Product, Engineering, Operations, and adjacent orgs (e.g., Growth, Ads).

This role is based in OpenAI's San Francisco HQ (in-office).

About the Role

As Data Science Manager, Integrity, you will lead a team of data scientists working across trust & safety, fraud prevention, risk analysis, measurement, and modeling. You will be accountable for building a high-performing data science function that can keep pace with fast-moving threats and for shaping the analytical strategy that informs how OpenAI detects, measures, and mitigates integrity risks at scale.

This is a highly cross-functional leadership role. You will help set the roadmap with Integrity Product and Engineering leaders, evolve team structure and operating rhythms, raise the bar on technical rigor (experimentation, causal inference, modeling, metrics), and develop a culture of proactive, high-leverage impact. The role requires strong judgment, comfort with ambiguity, and an ability to build systems that scale as new misuse patterns emerge.

Responsibilities

• Lead and scale a high-impact Integrity Data Science team: hiring, coaching, and developing ICs (and potentially future managers) while setting a strong technical and cultural bar.
• Drive strategy across multiple Integrity domains (policy enforcement, bot detection, fraud prevention, IP theft, risk measurement, abuse prevention), balancing near-term responses with durable systems.
• Build and institutionalize analytical rigor: metric frameworks, experimentation standards, monitoring/alerting, and repeatable evaluation approaches for Integrity interventions.
• Partner deeply with Product & Engineering to shape roadmaps, prioritize bets, and translate ambiguous risk signals into practical product and platform decisions.
• Evolve team structure and operating model as the org scales — define ownership boundaries, improve processes, and create leverage through tooling and AI-assisted workflows.
• Enable cross-org outcomes, supporting partners outside Integrity (e.g., Growth, Ads, GTM) where integrity risks intersect with product and business goals.
• Communicate clearly with senior leadership: synthesize tradeoffs, surface risk, and drive alignment on priorities and success metrics.
• Push the team toward an AI-leveraged operating mode, using modern tooling and model capabilities to accelerate detection, triage, analysis, and iteration.

Requirements

• Deep experience leading and scaling Data Science teams, ideally in trust & safety, fraud/abuse, security, risk, or other adversarial problem spaces in fast-moving environments.
• Strong technical grounding across modern data science techniques: experimentation, causal inference, anomaly detection, risk modeling, measurement design, and evaluation.
• Track record of building durable partnerships across Data Science, Engineering, Product, and Operations — able to influence without authority and create shared accountability.
• Proven ability to hire, mentor, and develop technical talent and to build a culture that is both high-bar and supportive.
• Ability to translate messy, evolving threats into clear frameworks, metrics, and decisions and keep the team focused on high-leverage work.
• Comfortable operating in ambiguity and able to bring structure, clarity, and momentum where the right answer isn't obvious.

Bonus

• Experience deploying scaled detection solutions using LLMs, embeddings, fine-tuning, or related ML systems for abuse/fraud/risk.
• Experience working closely with policy, content moderation, investigations, or security operations teams and designing analytics that work end-to-end.
• Experience building or leading measurement systems that balance safety, user experience, and operational/business constraints.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring general-purpose AI benefits all of humanity. The company emphasizes safety and inclusion and provides equal employment opportunities. Background checks will be administered where applicable. OpenAI is committed to providing reasonable accommodations to applicants with disabilities.

Benefits and Compensation

• Base pay range listed: $255K - $490K (offers also include equity and may include performance-related bonus and other components). The base pay may vary based on market location, job-related knowledge, skills, and experience.
• Medical, dental, and vision insurance with employer contributions to Health Savings Accounts.
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental leave, paid medical and caregiver leave, and flexible PTO policies.
• 13+ paid company holidays and additional coordinated company closures.
• Mental health and wellness support; employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily meals in offices and meal delivery credits as eligible.
• Relocation support for eligible employees.
• Additional taxable fringe benefits such as charitable donation matching and wellness stipends.

For more details, candidates are referred to company policies and benefit disclosures during the hiring process.