# Data Scientist, Inference Capacity Optimization at OpenAI

- Company: OpenAI
- Status: Open
- Workplace: Hybrid
- Location: San Francisco · Remote
- Level: Mid-level
- Discipline: Data
- Employment: Full-time
- Salary: $293K–325K
- Posted: 2026-09-15
- Skills: statistics
- Apply: https://jobs.ashbyhq.com/openai/4948533f-1df6-49f7-af9e-a2da0e02ebca

## Description

About the Role

OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models.

We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience.

You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments.

Key Responsibilities

 - Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency.

 - Develop forecasting models for inference demand across products, regions, and model families.

 - Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities.

 - Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies.

 - Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs.

 - Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions.

 - Collaborate with Product, Research, Finance, and Infrastructu

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