Data Scientist, Core Experimentation

Details

The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. The team partners with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable for frontier AI products.

The role focuses on improving the statistical rigor, reliability, and practical usability of OpenAI's core experimentation platform. It addresses online experimentation challenges including sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex machine learning systems.

This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices.

Responsibilities

• 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 while balancing statistical rigor with operational simplicity.
• Improve the reliability and trustworthiness of experiment results, including the detection and prevention of bias, logging issues, and data quality failures.
• Develop scalable 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 raise the overall technical bar for experimentation and causal inference.

Requirements

• 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 variance reduction, CUPED, sequential testing, sample ratio mismatch detection, metric design, or heterogeneous treatment effects.
• Strong coding and systems skills in Python and large-scale data processing frameworks such as Spark.
• Experience designing analytical data models and scalable experimentation pipelines.
• Ability to communicate complex statistical concepts clearly to technical and non-technical audiences.
• A track record of influencing technical strategy through hands-on technical leadership.
• Experience in large-scale product experimentation, machine learning experimentation, ranking systems, marketplace systems, or similar high-scale experimentation domains is highly valued.

Workplace And Location

This role is based in Bellevue and uses a hybrid work model, with in-person collaboration for technical design, iteration, and cross-functional partnership.

Compensation And Benefits

• Base salary: $293,000–$325,000 USD per year.
• Equity, performance-related bonuses for eligible employees, and benefits are included in total compensation.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental, medical, and caregiver leave.
• Paid time off, company holidays, office closures, and paid sick or safe time as required by applicable law.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily office meals and eligible meal delivery credits.
• Relocation support for eligible employees.