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. The Data Science team works on a wide variety of evaluation and modeling problems, including safety evaluation, the simulation technology, driving quality and rider experience. This role works with a variety of teams across the company to inject data science rigor and perspective, and to influence development direction in many of the critical systems in self-driving technology and fleet operations. As a Data Science intern, you may join one of these Data Science Subteams: - World Model Eval - Safety Eval Tech - Data Science Safety - Driving Quality Data Science - Simulation Data Science Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship! You will: - Analyze large-scale on-road and simulation data to build metrics, statistical models, and predictive features that quantify the Waymo Driver's safety and driving quality performance - Develop and validate statistical / ML methodology — estimation, uncertainty quantification, sampling, and extrapolation — to use or evaluate large-scale foundation models and draw reliable conclusions about rare and critical events from limited data - Build tools and pipelines that turn one-off analyses into repeatable workflows, partnering with engineering teams to automate data exploration, triage, and reporting You have: - Pursuing PhD in a quantitative field (e.g. Statistics, Computer Science, Mathematics, Physics, Engineering, Computational Social Science) - Proficiency in programming with Python (or R), including data manipulation, wrangling, and visualization - Strong statistical theory foundation We prefer: - Experience in machine learning applications and complex data analysis, or familiarity with SQL and/or C/C++ - Experience in processing and interpreting high dimensional data such as images/videos - Demonstrated research capabilities through publications and a strong understanding of statistical methodologies and foundation models - Prior internship experience (Autonomous Driving and generative AI preferred) General Perks - Help solve challenging problems with a direct impact on the company - Competitive compensation packages with a housing/relocation bonus (if applicable) - Medical, dental, and vision insurance - Fun intern events and networking opportunities Onsite Perks - Free breakfast, lunch, dinner, and snacks - Free access to Google shuttles - Onsite gym Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in. The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements. Hourly PhD Pay $85 — $85 USD