Analytics & Automation Lead, User Safety & Risk Operations
WFA Digital Insight
The demand for skilled analytics and automation professionals in the tech industry has grown significantly, with a 25% increase in job postings over the past year. As companies like Openai continue to prioritize user safety and risk management, the need for experts who can develop and implement effective analytics and automation systems has become more pressing. With the rise of remote work, candidates with strong technical and analytical skills, as well as experience in managing distributed teams, are in high demand. Openai's commitment to innovation and safety makes this role an attractive opportunity for those looking to make a meaningful impact in the industry. Before applying, candidates should be aware of the company's hybrid work model and the potential for exposure to sensitive content.
Job Description
About the Role
The Analytics & Automation Lead at Openai will play a critical role in managing and growing a senior technical operations team responsible for building analytics, automation, and quality systems that help User Safety and Risk Operations scale. This is a hands-on leadership role that requires a mission-oriented systems thinker who can translate complex operational problems into practical, measurable solutions. The ideal candidate will have a deep understanding of workflow automation, operational health analytics, and quality and evaluation systems.As a leader in this role, you will be responsible for setting the strategy and operating cadence for a horizontal team that supports safety and risk operations across multiple workflows and domains. You will prioritize a portfolio of high-impact opportunities, making clear tradeoffs based on user impact, risk reduction, operational need, technical feasibility, and scalability.
What You Will Do
- Lead and develop a senior team of technical and analytical ICs responsible for automation, analytics, reporting, and other systems.
- Set the strategy and operating cadence for a horizontal team supporting safety and risk operations across multiple workflows and domains.
- Prioritize a portfolio of high-impact opportunities, making clear tradeoffs based on user impact, risk reduction, operational need, technical feasibility, and scalability.
- Build systems that improve operational health and visibility, including data infrastructure, dashboards, SLA and backlog monitoring, and quality measurement.
- Design and implement workflow improvements such as automated triage, routing, prioritization, signal enrichment, case clustering, review assistance, and reporting automation.
- Build and improve the systems and strategies for emerging risk identification, analysis, and signal sharing.
- Identify where AI, LLMs, classifiers, or lightweight tooling can materially improve operational work, while designing appropriate evaluation, monitoring, human review, and fallback paths.
- Establish measurement and quality frameworks for operational systems, including golden sets, sampling strategies, reviewer calibration, false-positive and false-negative monitoring, and system-health metrics.
- Partner with operational teams as well as Product, Engineering, Product Policy, Safety, and Support to identify high-leverage opportunities and build practical systems that improve outcomes.
What We Are Looking For
- 5+ years of experience in a technical operations or analytics role, with a focus on building and managing high-performing teams.
- Strong technical skills, including proficiency in programming languages such as Python, Java, or C++.
- Experience with workflow automation, operational health analytics, and quality and evaluation systems.
- Excellent communication and leadership skills, with the ability to work effectively with cross-functional teams.
- Strong problem-solving skills, with the ability to analyze complex operational problems and develop practical solutions.
- Experience with AI, LLMs, classifiers, or lightweight tooling, and the ability to apply these technologies to improve operational work.
- Strong understanding of data infrastructure, including data warehousing, ETL, and data visualization.
Nice to Have
- Experience with cloud-based technologies such as AWS or Google Cloud.
- Familiarity with agile development methodologies and version control systems such as Git.
- Knowledge of machine learning or deep learning frameworks such as TensorFlow or PyTorch.
- Experience with data science tools such as Jupyter Notebooks or Apache Spark.
Benefits and Perks
- Competitive salary and benefits package.
- Opportunity to work with a cutting-edge technology company that is pushing the boundaries of AI and machine learning.
- Collaborative and dynamic work environment with a team of experienced professionals.
- Flexible work arrangements, including remote work options and flexible hours.
- Professional development opportunities, including training and education programs.
- Access to the latest technologies and tools, including AI and machine learning frameworks.
- Comprehensive health and wellness programs, including mental health support and employee assistance programs.
How to Stand Out
- Develop a strong understanding of workflow automation, operational health analytics, and quality and evaluation systems to stand out as a candidate.
- Showcase your experience with AI, LLMs, classifiers, or lightweight tooling, and demonstrate how you can apply these technologies to improve operational work.
- Highlight your leadership skills and experience in managing high-performing teams, and be prepared to provide specific examples of your accomplishments.
- Be prepared to discuss your approach to problem-solving and analytics, and provide examples of how you have used data to drive business decisions.
- Research the company's hybrid work model and be prepared to discuss your experience with remote work and flexible arrangements.
- Be aware of the potential for exposure to sensitive content and be prepared to discuss your approach to handling sensitive information.
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