Sr. Product Data Scientist, Planning

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 the Director, Product Data Science.

You will:

• Work with cross functional teams to make long-term decisions related to vehicle allocation, capital investment, and long-term growth planning.


• Develop forecasting models that measure the impact of long-term investments on key business metrics.


• Build optimization models to choose the allocation of vehicles and infrastructure across markets.


• Conduct deep dive analysis to identify areas for future improvement.

You have:

• At least 3 years of industry experience.


• Coding skills (Python & SQL).


• Strong communication and stakeholder & management skills.


• ML, causal inference, and optimization algorithm experience.


• Experience working with the product management and engineering teams.


• Proficiency in data pipeline development.

We prefer:

• Experience with causal inference, optimization, and/or forecasting.