Staff Data Scientist, Weather

Job description

Job 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.
• 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.
• 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 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.

Job 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.