Data Scientist, Platform and B2b Products

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

Data Scientist on the Platform team at OpenAI, focusing on API and B2B solutions. The role involves defining metrics, measuring impact, and partnering with product and engineering to improve model quality, reliability, latency, and cost, ultimately shaping the adoption of agentic AI.

What you'd actually do

  1. Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth
  2. Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models
  3. Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products)
  4. Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams
  5. Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality)

Skills

Required

  • 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus)
  • Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments
  • Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety)
  • Strong cross-functional communication with PMs, engineers, and executives
  • Strategic instincts beyond p-values—clear thinking about tradeoffs and business impact

Nice to have

  • Background in developer platforms, observability, or usage-based pricing/quotas
  • Experience connecting offline evals to online product impact
  • Prior work in NLP/LLMs or agentic systems, or in enterprise analytics for B2B products

What the JD emphasized

  • latency/cost guardrails
  • reliability
  • latency
  • cost
  • reliability/latency/cost
  • offline evals to online product impact

Other signals

  • drive a data-driven culture for OpenAI’s API and B2B solutions
  • measure the impact of new models and features
  • improve model quality, reliability, latency, and cost
  • shape how thousands of products adopt agentic AI