Why This Job is Featured on The SaaS Jobs
This role stands out in the SaaS ecosystem because inference capacity has become a core constraint for AI-enabled products delivered as services. The remit sits at the intersection of product demand and platform supply, translating usage patterns into decisions about latency, throughput, and global fleet allocation. In a market where reliability and unit economics are tightly coupled, the ability to quantify trade offs in serving infrastructure is increasingly strategic.
For a SaaS career, the work builds durable skills in operating data science against production systems rather than offline analytics. Forecasting demand across regions and model families, designing simulations, and creating operational metrics are experiences that transfer to any subscription business managing variable usage, SLOs, and cost to serve. The cross functional partnerships described also mirror how mature SaaS organizations make planning decisions, with analytics informing engineering roadmaps and investment timing.
This position is best suited to data scientists who prefer systems oriented problem framing and are comfortable turning messy operational telemetry into decision ready models. It will fit professionals who like stakeholder heavy work and can communicate uncertainty clearly, especially when recommendations influence long horizon capacity planning. A background in forecasting, optimization, or infrastructure analytics maps naturally to the day to day focus.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job 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 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
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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