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 operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. The mission is to help teams make better decisions through reliable experimentation, emphasizing statistical correctness, pragmatic solutions, and scalable systems that researchers and engineers can trust.

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, balancing rigor with operational simplicity.
• Improve reliability and trustworthiness of experiment results, including 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 (e.g., CUPED), sequential testing, sample ratio mismatch (SRM) detection, metric design, triggered analysis, and heterogeneous treatment 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 and uses a hybrid work model valuing in-person collaboration for technical design, iteration, and cross-functional partnership.

Compensation Range

$293,000 - $325,000 USD (base pay). In addition to base pay, total compensation may include equity, performance-related bonuses for eligible employees, and other benefits.

Benefits

• Medical, dental, and vision insurance with employer contributions to Health Savings Accounts
• Pre-tax accounts (Health FSA, Dependent Care FSA, commuter accounts)
• 401(k) with employer match
• Paid parental leave and paid medical/caregiver leave
• Paid time off (flexible PTO for exempt employees) and paid company holidays
• Mental health and wellness support
• Employer-paid basic life and disability coverage
• Annual learning and development stipend
• Daily meals in offices and meal delivery credits as eligible
• Relocation support for eligible employees
• Additional taxable fringe benefits such as charitable donation matching and wellness stipends

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The company emphasizes safety, diverse perspectives, and inclusion, and is an equal opportunity employer. Background checks are administered in accordance with applicable law. Reasonable accommodations for applicants with disabilities are available.