# Data Scientist, Inference Capacity Optimization

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** Data Science
**Salary:** $293k – $325k/yr
**Experience:** 5+ years
**Skills:** Python, SQL, Forecasting, Machine Learning, Statistical Modeling, optimization, time-series analysis, operations research, Reinforcement Learning, queueing theory, causal analysis, Experimentation, Distributed Systems, Capacity Planning
**Posted:** 2026-07-27

> Data Scientist optimizing inference capacity on OpenAI's global GPU fleet. Build statistical/ML forecasting models, analyze workloads for bottlenecks, design experiments for scheduling/serving tradeoffs, and partner with engineering to guide infrastructure investments and efficiency improvements. Requires MS/PhD and 5+ years in infrastructure data science.

## Job Description

## 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 Infrastructure teams to align compute planning with business growth and model roadmaps.
- Communicate technical findings clearly to both engineering teams and executive leadership.

## Qualifications
- MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience).
- 5+ years of experience working in the infrastructure data science space.
- Strong expertise in Python and SQL.
- Experience building forecasting, optimization, or predictive models.
- Strong understanding of experimentation, statistical inference, and causal analysis.
- Experience communicating analytical insights to executive stakeholders.

## Preferred Skills
- Capacity planning
- Distributed systems
- AI infrastructure
- Datacenter design and buildout
- Queueing theory
- Time-series forecasting
- Operations research
- Supply-demand modeling
- Reinforcement learning for resource allocation
- Cost optimization

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