Data Scientist, Safety Systems

OpenAI OpenAI · AI Frontier · San Francisco, CA · Data Science

The Data Scientist, Safety Systems role focuses on establishing a data-driven approach to understand, evaluate, and monitor the safety of production AI systems. This involves defining and implementing metrics, creating dashboards, and collaborating with researchers and engineers to ensure safe AI deployment. The role emphasizes leadership in quantitative analysis and metric operationalization within a safety-focused team.

What you'd actually do

  1. Lead our efforts in understanding and measuring the real-world safety impacts of OpenAI’s current and upcoming products
  2. Uncovering new ways to improve our approaches to measuring and mitigating harm and abuse
  3. Develop and implement statistical methods necessary to operationalize safety-related metrics
  4. Provide direction, guidance, and coordination of projects in the space
  5. Establish a data-driven culture within Safety Systems by driving the definition, tracking, and operationalizing of feature-, product-, and company-level metrics

Skills

Required

  • 5+ years experience in a quantitative role
  • navigating highly ambiguous environments
  • founding data scientist or team lead experience
  • leadership skills
  • leading multiple data scientists and cross-functional teams
  • Expertise in defining and implementing metrics
  • track record of operationalizing new feature and product-level metrics from scratch
  • Excellent communication skills
  • ability to communicate with product managers, engineers, and executives
  • Strategic insights
  • statistical significance testing

Nice to have

  • Experience in trust and safety, integrity, anti-abuse, or related fields
  • Demonstrated prior experience in NLP, large language models, or generative AI
  • Strong statistical background, including knowledge of sampling, regression, causal analysis, and more

What the JD emphasized

  • safety
  • metrics
  • evaluate
  • monitoring
  • production systems
  • harm and abuse
  • statistical methods
  • operationalize
  • data-driven culture
  • safety-related questions
  • safety research
  • training
  • evaluation
  • quantitative role
  • ambiguous environments
  • founding data scientist
  • team lead
  • hyper-growth product company
  • research org
  • leadership skills
  • leading multiple data scientists
  • cross-functional teams
  • defining and implementing metrics
  • operationalizing new feature and product-level metrics
  • communication skills
  • product managers
  • engineers
  • executives
  • strategic insights
  • statistical significance testing
  • trust and safety
  • integrity
  • anti-abuse
  • NLP
  • large language models
  • generative AI
  • statistical background
  • sampling
  • regression
  • causal analysis

Other signals

  • safety
  • metrics
  • evaluation
  • production systems
  • data-driven