Staff Data Scientist, Weather

Waymo•San Francisco, CA

37d•Hybrid

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. Rigorous evaluation of the Waymo Driver, including monitoring the performance of Waymo’s fleet in the field, is a critical part of scaling our ride hailing service and achieving Waymo’s ambitious goals. In this role, you will lead key initiatives for modeling weather patterns and their impact on Waymo’s ride hailing service, and streamlining Waymo’s operational procedures designed to mitigate weather-related challenges in real time and measuring the performance of the Waymo Driver in adverse weather conditions. In this hybrid role you will report to the Data Science Lead for Driving Quality & Scope Expansion.

Requirements

Degree in a quantitative field (e.g. Statistics, Mathematics, Physics).
Either a PhD in a quantitative field and 8+ years of industry experience, or 12+ years of industry experience solving data science problems.
Experience working with and building models for spatio-temporal data.
Experience as a technical lead.
Experience working in highly cross-functional teams and championing data-driven culture.
Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models.
Demonstrated knowledge of data analysis libraries and packages in Python, R, and/or SQL.

Nice To Haves

PhD in a quantitative, weather-adjacent field (Atmospheric Science, Meteorology, Hydrology, etc.), and/or academic experience developing and applying statistical methods in those fields.
Experience working with third-party (e.g., public / private) weather data sources and integrating multiple data sources.
Experience solving problems related to weather modeling or prediction.
A demonstrated track record of independently driving data science projects to deliver business value.
Experience with large-scale evaluation frameworks for software development.

Responsibilities

Define and uphold a high bar for measurement rigor.
Ensure we can confidently rely on the evaluation signals informing deployment, scaling, and mitigation decisions.
Identify and work to resolve any gaps where current evaluation signals are not scaling with Waymo’s business or providing the necessary actionability for stakeholders.
Build pipelines and models integrating a range of existing and novel weather-specific data sources (1P/2P/3P) to enhance Waymo’s weather intelligence and prediction capabilities.
Measure the performance of the Waymo driver in adverse/extreme weather conditions (fog, rain, snow, ice, hail, flooding), providing input on Waymo’s readiness to scale in challenging weather contexts.
Communicate these findings to senior stakeholders.
Develop scalable and repeatable analysis frameworks that support multiple climate types, both domestically and internationally.
Optimize Waymo’s operational processes for addressing adverse/extreme weather across a wide range of geographical territories, making them smarter, more responsive, and more efficient.
Develop a deep understanding of Waymo’s long-term roadmap, and collaborate with leads in product, engineering, and systems engineering to unlock key deployment milestones.
Be an opinionated partner influencing roadmaps for engineering work to improve our measurement capabilities.
Be an active technical contributor on the team, as well as a technical lead to junior data scientists.
Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods.
Champion data science excellence and provide constructive technical feedback within the team and across Waymo.