Technical Operations Analyst, User Safety & Risk

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. Within USRO, Risk Incubation & Systems builds the analytics, automation, monitoring, quality mechanisms, and operating systems that help teams identify risk, make sound decisions, and scale safely. Our work spans emerging-risk detection, operational measurement, workflow automation, quality systems, launch readiness, and decision-support tools. We partner closely with operational teams as well as Product, Engineering, Data Science, Product Policy, Safety, Legal, and Support to identify high-leverage opportunities and build practical systems that improve outcomes. About the Role We are hiring a Technical Operations Analyst to solve ambiguous, high-impact operational problems using data, technical tools, and strong judgment. You will work as an experienced individual contributor across USRO, moving from problem definition through analysis, workflow design, implementation, measurement, and handoff. The scope is intentionally broad and may span emerging-risk detection, operational quality, automation, launch readiness, and other priority programs. You will be expected to move between different problem areas as organizational needs evolve. This is a hands-on role. You should be comfortable querying and validating data, building dashboards and lightweight automations, using AI tools to accelerate work, and working directly with operators and technical partners to turn incomplete information into practical systems. Your work may also include data and operational monitoring issues for major cloud deployment partnerships—for example, validating pipelines and safety signals, investigating anomalies or discrepancies, improving reporting and escalation mechanisms, and documenting data limitations so partner teams can act with confidence. Location / work model: London, UK; hybrid, 3 days/week in-office. Please note: This role may involve exposure to sensitive or concerning content. Strong discretion, judgment, and resilience are essential. In This Role, You Will Independently scope ambiguous operational problems and frontier & emerging risks, and turn them into clear analyses, workflows, tools, or decision systems. Analyze large and complex datasets to identify patterns, data-quality gaps, operational blind spots, and source-of-truth issues. Build and maintain dashboards, monitoring, alerts, recurring reporting, and workflow automations. Develop systems for detecting and assessing emerging risks, including classifier, evaluation, labeling, and human-review feedback loops. Support major cloud deployments and partnerships by validating data pipelines and safety signals, investigating anomalies, and improving operational monitoring, reporting, and escalation. Design practical quality controls such as sampling plans, golden datasets, validation holdouts, thresholds, human review, and fallback paths. Use AI and LLM-based tools to improve speed and scale while applying appropriate testing, quality assurance, and human oversight. Translate technical and operational findings into clear recommendations, tradeoffs, decisions, and next steps for partner teams. Partner across Operations, Product, Engineering, Data Science, Product Policy, Safety, Legal, and Support to define ownership, requirements, and durable handoffs. Document system logic, limitations, operating procedures, and maintenance expectations so others can run and improve the work. You Might Thrive in This Role If You Have 5+ years of experience in technical operations, data analytics, trust and safety, risk operations, product operations, or a related field. Are strong in SQL and comfortable working with unfamiliar datasets, schemas, joins, denominators, and data-quality issues. Have built practical dashboards, tools, automations, or operating systems and owned them from initial scoping through adoption and maintenance. Can use AI and LLM tools to accelerate real workflows while independently validating outputs and managing failure modes. Understand how to measure technical or operational systems using concepts such as precision, recall, coverage, error analysis, quality assurance, and human review. Exercise sound judgment in scaled operations, including queues, escalations, reviewer workflows, capacity, quality, and incident response. Move quickly in ambiguous environments, make thoughtful tradeoffs, and create structure without waiting for perfect requirements. Communicate complex findings clearly to technical, operational, and leadership audiences and drive work through cross-functional partners. Nice to Have Experience in trust and safety, fraud, scaled or adversarial abuse, integrity, emerging-r