Product Data Scientist, Operation Center

WaymoSan Francisco, CA
2dHybrid

About The Position

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 the Manager of Product Data Science.

Requirements

  • Coding skills (Python and SQL)
  • Experience with Modeling and Optimization
  • At least 8 years of industry experience
  • Strong Communication and Stakeholder & Management skills

Nice To Haves

  • Experience with Experimentation
  • Previous experience with Call Centers and queuing theory

Responsibilities

  • Develop and deploy statistical models to determine optimal staffing levels, ensuring rapid response times to AV and rider inquiries while upholding Waymo's safety standards
  • Collaborate with Engineering to design and implement optimization models for request prioritization and queuing, driving cutting-edge scalability for operations
  • Conduct deep-dive data analysis and trend evaluation to identify and execute on opportunities to improve Operations Center efficiency and customer experience
  • Partner with Product and Operation to define metrics, measurement framework, and be a promoter of experimentation
  • Build and maintain robust data foundations and reporting infrastructure
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