Waymo is an autonomous driving technology company with a mission to make it safe and easy for people and things to get where they’re going. Since our start as the Google Self-Driving Car Project in 2009, Waymo has been focused on building the World’s Most Experienced Driver in hopes of improving the world's access to mobility while saving thousands of lives now lost to traffic crashes. Our Waymo Driver powers Waymo One, our fully autonomous ride-hailing service, as well as Waymo Via, our trucking and local delivery service. To date, Waymo has driven over 20 million miles autonomously on public roads across 25 U.S. cities and conducted over 20 billion miles of simulation testing.
The Waymo Safety team works to promote and help to continuously improve the safety of Waymo’s fully autonomous driving technology. Our experts develop safety goals and strategies, and conduct safety engineering analyses to ensure safety is being considered throughout the design and development of our vehicles. The team develops and promotes safety strategies and policies for autonomous vehicles for its work with regulatory authorities, lawmakers, law enforcement and public and non-profit organizations. Our Safety Team also helps advise on compliance with applicable environmental, health, and safety regulations. Within the Safety Research and Best Practices team, we conduct research on autonomous driving safety by drawing on established vehicle safety knowledge and methods. We conduct novel research to develop safety methodologies, perform structured analysis, and disseminate results on key safety-related questions.
In this role, you'll:
- Work closely with data science, systems, and engineering teams to identify collision surrogate measures to predict automotive crash-involvement, and develop/further metrics for robust risk and exposure predictions
- Be a chief contributor in the statistical analyses of autonomous driving data, naturalistic driving data, and crash databases to ground the evaluation of autonomous driving performance
- Support the Waymo Safety Team to oversee the program safety readiness process and metrics from an collision-epidemiological perspective
- Contribute to the continuous improvement of the robustness of Waymo’s safety framework
At a minimum we’d like you to have:
- Master’s of Science in the physical or data sciences, or a related technical degree, with a strong background in statistical analysis of traffic data
- Strong fundamental knowledge in probability theory and statistics
- 10+ years of relevant work experience in applied research regarding traffic conflicts, naturalistic driving data analysis, and/or injury epidemiology
- Proven publication track record in the field of vehicle/traffic safety research, collision epidemiology or surrogate metrics
- Proficiency in providing underlying basis of collision risk assessment through classification/measurement of driving exposure and crash frequency
- Proficiency in understanding and analyzing crash and naturalistic databases
- Fluency in quantitative analysis/modelling tools
- Strong presentation skills to effectively communicate findings to technical and non-technical audiences alike
It is preferred that you have:
- A Ph.D in the data or technical sciences
- Considerable experience in building models using Monte-Carlo, Bayesian, and/or Extreme Value Theory methodologies
- Strong background in study design
- Ability to use python, SQL, or C++ to interface with Waymo-internal driving- and simulation data sources to conduct research
We appreciate your interest in Waymo. Waymo is an equal employment opportunity employer. Waymo’s policy is not to discriminate against any applicant or employee based on race, color, sex, religion, national origin, age, disability, military status, genetic information or any other characteristic protected by law. Waymo also prohibits harassment of applicants or employees based on any of these protected categories. Waymo will also consider for employment qualified applicants with criminal records in accordance with applicable law. Waymo also makes workplace accommodations for qualified individuals with disabilities as required by applicable law.