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About the Role
Waymo's Product Data Science team collaborates with Engineering, Product, and Operations to drive informed decisions using data. This team works on high-impact projects, from improving driving quality and operational efficiency to analyzing market trends and rider satisfaction, all to safely and efficiently scale the Waymo Driver.
Responsibilities
- 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.
Requirements
- 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.
Skills
- Python
- SQL
- ML
- Causal Inference
- Optimization Algorithms
- Data Pipeline Development
Location
- US
Work Type
- Hybrid
- Full-time
Experience Level
- 3+ years of industry experience
Salary/Compensations
- $196,000—$242,000 USD
Benefits
- Discretionary annual bonus program
- Equity incentive plan
- Generous Company benefits program
About the Company
- 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.