Staff Product Data Scientist, Experimentation

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

Waymo’s Product Data Science team works cross-functionally with Engineering, Product and Operations to help the company make the most informed decisions using data. Our team collaborates on high-impact projects across the company — from driving quality and operational efficiency to market analysis and rider satisfaction scores — we help to safely and efficiently scale the Waymo Driver. We are data-driven, curious, open-minded, and adapt quickly to new information.

In this hybrid role, you will report to a Staff Product Data Scientist.

You will:

• Define the science roadmap for Waymo’s marketplace experimentation platform


• Develop advanced testing methodologies to solve for physical-world dynamics like network effects and spatial-temporal correlations


• Establish rigorous best practices for experiment design and evaluation across the broader product organization


• Partner with engineering to translate algorithmic logic into automated, production-grade pipelines


• Act as the primary domain expert on causal inference, providing technical leadership and translating complex results into clear product strategy

You have:

• An advanced degree in a quantitative field (e.g., Statistics, Economics, Operations Research, Computer Science)


• 8+ years of industry experience with a deep focus on causal inference, experimental design, and applied statistics


• Proficiency in SQL and Python, with a track record of partnering with engineering to build automated experimentation tools


• Strong product sense and the ability to explain technical concepts to non-technical stakeholders

We prefer:

• Experience with two-sided marketplaces and physical-world operations (e.g., ride-hailing, delivery)


• Familiarity with core marketplace systems (e.g., pricing, matching)


• Experience integrating algorithmic methods into large-scale internal platforms