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OpenAI's User Operations organization is building the data and intelligence layer behind AI-assisted operations to transform customer support and improve product and user experience at scale by leveraging human-AI collaboration.

Requirements

• Expertise in statistics and causal inference, applied in both experimentation and observational causal inference studies.
• Expert-level SQL and proficiency in Python for analytics, modeling, and experimentation.
• Proven experience designing and interpreting experiments and making statistically sound recommendations.
• Experience building data systems or pipelines that power production workflows or ML-based decisioning.
• Experience developing and extracting insights from business intelligence tools, such as Mode, Tableau, and Looker.
• Familiarity with large language models or AI-assisted operations platforms.
• Background in experimentation infrastructure or human-AI interaction systems.

Responsibilities

• Build and own metrics, classifiers, and data pipelines that determine automation eligibility, effectiveness, and guardrails.
• Design and evaluate experiments that quantify the impact of automation and AI systems on user outcomes like resolution quality and satisfaction.
• Develop predictive and statistical models that improve how OpenAI’s support systems automate, measure, and learn from user interactions.
• Partner with engineering and product teams to create feedback loops that continuously improve our AI agents and knowledge systems.
• Develop and socialize dashboards, applications, and other ways of enabling the team and company to answer product data questions in a self-serve way
• Contribute to establishing data science standards and best practices in an AI-native operations environment.
• Partner with other data scientists across the company to share knowledge and continually synthesize learnings across the organization

Other

• 10+ years of experience in data science roles within product or technology organizations.
• Strategic and impact-driven mindset, capable of translating complex business problems into actionable frameworks.
• Ability to build relationships with diverse stakeholders and cultivate strong partnerships.
• Strong communication skills, including the ability to bridge technical and non-technical stakeholders and collaborate across various functions to ensure business impact.
• Ability to operate effectively in a fast-moving, ambiguous environment with limited structure.