<div><p>Waymo is an autonomous driving technology company with the mission to be the worlds most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The Worlds 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.</p></div><p>The Safety Evaluation team stands as the gatekeepers of safety, weaving expertise in data analysis and robust validation into the very fabric of our autonomous driving systems. We collaborate closely with engineers to ensure the evaluation of ML-heavy-systems rests on a foundation of safety principles. Our expertise seeps into every layer of our safety-critical systems, ensuring each decision made by our vehicles is rooted in rigorous analysis and sound judgment. Our work extends beyond assessment, venturing into the realm of innovation as we craft novel ML techniques uniquely tailored to the complexities of collision evaluation. Ultimately, our team paves the way for safer roads and a future where Waymo diver glides confidently through the complexities of the real world.</p> <p>As a Staff Data Scientist specializing in Safety Evaluation at Waymo, youll play a critical role in ensuring the safety and reliability of autonomous vehicles. Your responsibilities will span the entire spectrum of data analysis, model development, and evaluation. While each day at Waymo is different, your primary responsibilities will include: </p> <ul> <li>Develop safety evaluation frameworks that are critical to ML model improvements.</li> <li>Design and implement robust data analysis pipelines and validation frameworks.</li> <li>Develop and apply statistical methods and ML models to analyze historical/simulation data and assess safety performance.</li> <li>Collaborate with cross-functional teams like Simulation and Planning to ensure comprehensive safety evaluation across the autonomous driving system.</li> </ul> <p>At a minimum we’d like you to have:</p> <ul> <li>PhD in a quantitative field (IE Statistics, Mathematics, Physics)</li> <li>7+ years of industry experience solving large-scale complex problems</li> <li>Proven expertise using advanced statistical methods (e.g., ML models, hypothesis testing, causal analysis)</li> <li>Ability to interpret and work with data in the presence of ambiguity (e.g., confounding factors, data sparsity or quality challenges)</li> <li>Demonstrated knowledge of Python/SQL/R data analysis libraries and packages</li> <li>Ability to take ambiguous and complex business requirements and propose a technical solution</li> </ul> <p>It’s preferred if you also have:</p> <ul> <li>Experience solving problems related to Autonomous Driving</li> <li>Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction</li> <li>Hands-on experience with Google infra tools like PLX, Borg, GCL, etc</li> </ul> <p>#li-hybrid</p><div><div><div><p><span>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. </span></p> <p><span>Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. </span></p></div><div>Salary Range</div><div><span>$238,000</span><span>—</span><span>$302,000 USD</span></div></div></div>