Why This Job is Featured on The SaaS Jobs
This Data Scientist role sits at a core SaaS concern: making product decisions measurable, comparable, and trustworthy through a shared experimentation platform. Rather than focusing on a single feature area, the remit is the underlying system that many teams rely on, spanning methodology, instrumentation reliability, and the practical constraints of running experiments across complex AI-driven products.
For a SaaS career, platform-level experimentation work builds durable leverage. It develops judgment around metric design, causal inference tradeoffs, and the failure modes that appear only at scale, such as data quality issues and biased logging. The role also reinforces a systems mindset, translating statistical ideas into tools that engineers and product teams can operate, which is a differentiator in SaaS environments where analytics must be embedded into product workflows.
This position is best suited to an experienced individual contributor who prefers deep technical ownership with broad cross-functional influence. It fits someone motivated by rigor and operational pragmatism, comfortable investigating ambiguous measurement anomalies, and interested in shaping how an organization standardizes decision-making rather than optimizing one dashboard or funnel in isolation.
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 Team
The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products.
Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics.
We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era.
About the Role
We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI’s core experimentation platform. This role is focused on improving the statistical rigor, reliability, and practical usability of experimentation across the company.
You’ll work on some of the hardest problems in online experimentation: sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex ML systems. You’ll also help translate advanced statistical concepts into pragmatic systems and product experiences that teams can actually use.
This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices. The ideal candidate combines deep statistical expertise with strong systems intuition and hands-on experience building or operating experimentation platforms at scale.
In this role, you will:
Drive the statistical direction and technical strategy for OpenAI’s experimentation platform
Design and improve experimentation methodologies used across product and research teams
Build pragmatic solutions to real-world experimentation challenges, balancing rigor with operational simplicity
Improve the reliability and trustworthiness of experiment results, including detection and prevention of bias, logging issues, and data quality failures
Developscalable analytical systems and pipelines in Python and distributed compute environments
Partner with engineers and product teams to improve experiment design, metric quality, and decision-making practices
Lead investigations into complex experimentation anomalies and measurement failures
Establish best practices for experimentation governance, interpretation, and statistical correctness
Mentor other data scientists and raising the overall technical bar for experimentation and causal inference
You might thrive in this role if you have:
Experience building, scaling, or operating experimentation platforms at a large technology company
Deep expertise in statistics, causal inference, and online experimentation methodology
Strong understanding of practical experimentation challenges in production systems
Experience with areas such as variance reduction, CUPED, sequential testing, SRM detection, metric design, or heterogeneous effects
Strong coding and systems skills in Python and large-scale data processing frameworks (e.g. Spark)
Experience designing analytical data models and scalable experimentation pipelines
Ability to communicate complex statistical concepts clearly to technical and non-technical audiences
Track record of influencing technical strategy through hands-on technical leadership
Experience in large-scale product experimentation, ML experimentation, ranking systems, marketplace systems, or similar high-scale experimentation domains is highly valued
Workplace & Location
This role is based in Bellevue. We use a hybrid work model and value in-person collaboration for technical design, iteration, and cross-functional partnership.
Compensation Range: $293K - $325K USD
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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