About the role
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.
This role follows a hybrid work schedule and you will report to a Product Data Science Lead
You will
- Partner with Engineering, Product, and Data Science to build ML models that improve the efficiency of Waymo's marketplace
- Build models that predict conversion, wait times, and retention, and estimate the value of a vehicle in different positions
- Apply forecasting models for demand and supply time series
- Develop novel reinforcement learning models that continuously tune pricing, matching, and positioning parameters
- Design, run, and evaluate experiments for new models
- Present findings and recommendations to Waymo leadership on a regular basis
You have
- 8+ years of industry experience applying ML to production problems
- Strong foundation in algorithms
- Proficiency in Python and SQL
- Hands-on experience building and deploying ML and neural network models
- Experience applying reinforcement learning to real-world systems
We prefer
- Experience building neural networks in TensorFlow, or JAX
- Experience at a ride-hailing or two-sided marketplace company
- MS or PhD in Computer Science, Statistics, Operations Research, or a related field
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.