Waymo Product Data Scientist - Optimization
Waymo is an autonomous driving technology company with the mission to be the 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 and save lives. The Waymo Driver powers Waymo One, a fully autonomous ride-hailing service, and can be applied across various vehicle platforms and use cases. It has completed over one million rider-only trips and driven tens of millions of miles on public roads across 13+ U.S. states.
Our Product Data Science team collaborates with Engineering, Product, and Operations teams to make data-informed decisions. We work on high-impact projects such as driving quality, operational efficiency, market analysis, and rider satisfaction to safely and efficiently scale the Waymo Driver. We are data-driven, curious, open-minded, and adaptable.
Role Overview
This hybrid role reports to a Product Data Science Lead, Optimization.
Responsibilities
- Partner with Engineering, Product, and Data Science teams to develop Matching and Positioning models for Waymo.
- Apply machine learning models to predict customer wait times and analyze vehicle values in different positions.
- Implement optimization models to assign Waymo vehicles to customers or positioning locations efficiently.
- Design, conduct, and evaluate experiments on new models.
- Present findings regularly to Waymo leadership.
Qualifications
- Statistical knowledge.
- Coding skills in Python and SQL.
- Experience with machine learning and reinforcement learning models.
- Experience with experimentation methodologies.
- Minimum of 4+ years of industry experience.
Preferred Skills
- Experience with optimization modeling and solvers like CP-SAT, CPLEX, Gurobi.
- Prior experience at ride-hailing or marketplace companies.
Compensation & Benefits
The base salary range for this full-time role across US locations is $196,000 — $248,000 USD. Actual pay depends on location, experience, training, and skills. Employees are eligible for annual bonuses, equity incentives, and comprehensive benefits.
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