技术运营分析师，用户安全与风险
Technical Operations Analyst, User Safety & Risk
关于团队
在OpenAI，用户安全与风险运营（USRO）团队帮助保护我们的产品和用户免受滥用、欺诈、安全风险和其他形式的误用。我们在现实世界的安全和风险管理的最前线运作，将用户和运营信号转化为及时的决策、有效的干预措施以及系统改进。
在USRO中，风险孵化与系统团队构建分析、自动化、监控、质量机制和操作系统，帮助团队识别风险、做出明智的决策并安全地扩展。
我们的工作涵盖新兴风险检测、运营度量、流程自动化、质量系统、发布准备和决策支持工具。我们与运营团队以及产品、工程、数据科学、产品政策、安全、法律和支持团队紧密合作，识别高影响力的机会，并构建实用的系统以改善结果。
职位描述
我们正在招聘一名技术运营分析师，利用数据、技术工具和良好的判断力解决模糊且影响重大的运营问题。你将作为经验丰富的个人贡献者在USRO内工作，从问题定义到分析、流程设计、实施、测量和交接。
该职位的范围有意保持广泛，可能涉及新兴风险检测、运营质量、自动化、发布准备和其他优先项目。你将根据组织需求的变化，在不同的问题领域之间切换。
这是一个需要动手操作的职位。你应该能够查询和验证数据，构建仪表板和轻量级自动化，使用AI工具加速工作，并直接与操作员和技术合作伙伴合作，将不完整的信息转化为实用的系统。
你的工作还可能包括主要云部署合作伙伴的数据和运营监控问题——例如，验证数据管道和安全信号，调查异常或差异，改进报告和升级机制，并记录数据限制，以便合作伙伴团队能够自信地采取行动。
地点/工作模式：英国伦敦；混合办公，每周3天在办公室。
请注意：此职位可能涉及接触敏感或令人担忧的内容。强大的判断力、谨慎和韧性是必不可少的。
在此职位中，你将
- 独立界定模糊的运营问题和前沿及新兴风险，并将其转化为清晰的分析、流程、工具或
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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-risk detection, or other high-stakes operational domains.
- Experience supporting cloud, enterprise, or privacy-preserving deployments with constrained data access or specialized monitoring requirements.
- Experience with classifiers, evaluations, golden datasets, labeling programs, reviewer calibration, or model-quality measurement.
- Experience with Python, notebooks, data-pipeline troubleshooting, or other lightweight technical development.
- Experience designing quality systems or workflows that involve vendors, BPOs, or distributed operational teams.
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.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.
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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