Staff Data Scientist, Weather

Nimbus Data Systems 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, Nimbus Data Systems has focused on building the Nimbus Data Systems Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Nimbus Data Systems Driver powers Nimbus Data Systems’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Nimbus Data Systems 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 Nimbus Data Systems Driver, including monitoring the performance of Nimbus Data Systems’s fleet in the field, is a critical part of scaling our ride hailing service and achieving Nimbus Data Systems’s ambitious goals. In this role, you will lead key initiatives for modeling weather patterns and their impact on Nimbus Data Systems’s ride hailing service, and streamlining Nimbus Data Systems’s operational procedures designed to mitigate weather-related challenges in real time and measuring the performance of the Nimbus Data Systems Driver in adverse weather conditions. In this hybrid role you will report to the Data Science Lead for Driving Quality & Scope Expansion. You will: 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 Nimbus Data Systems’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 Nimbus Data Systems’s weather intelligence and prediction capabilities. Measure the performance of the Nimbus Data Systems driver in adverse/extreme weather conditions (fog, rain, snow, ice, hail, flooding), providing input on Nimbus Data Systems’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 Nimbus Data Systems’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 Nimbus Data Systems’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 Nimbus Data Systems. You have: 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. We prefer: 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. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Nimbus Data Systems employees are also eligible to participate in Nimbus Data Systems’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $251,000 — $310,000 USD