Sr. Staff Data Scientist, TLM, Driving Quality
Waymo - Mountain View, California, USA
Posted Sep 16, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- 401(k) match
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Schedule
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- Weekend work
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Application
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Where they hire
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About this role
Sr. Staff Data Scientist, TLM, Driving Quality Mountain View, California, USA 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 Driverâ„¢-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. Rigorous evaluation of the Waymo Driver is a critical part of scaling our ride hailing service and achieving Waymo's ambitious goals. In this role, you will lead a data science team specializing in evaluating the Waymo Driver's ability to comply with rules of the road. Road rule-related behaviors are some of the most challenging to identify, and areas of work include understanding human baseline performance, partnering with ML engineers to improve detection capabilities, and delivering critical insight about the Driver's current capabilities and opportunities for improvement. In this hybrid role you will report to the DS Lead for Driving Quality. You will: - Define and uphold a high bar for measurement rigor. Ensure we can confidently rely on the evaluation signals informing deployment and scaling decisions. Identify and
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