Data Science Intern (2027 Summer, PhD)
Waymo
San Francisco, United States Posted September 27, 2026
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Job Description
Join Waymo, a leader in self-driving technology, as a Data Science Intern for the summer of 2027. In this role, you will work on a variety of evaluation and modeling problems, including safety evaluation, simulation technology, driving quality, and rider experience. You will collaborate with various teams across the company to inject data science rigor and influence development direction in critical systems. This is a hybrid onsite internship position with numerous benefits, including medical, dental, and vision insurance, competitive compensation, and opportunities for professional growth.
- Analyzing 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.
- Developing and validating 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.
- Building tools and pipelines that turn one-off analyses into repeatable workflows, partnering with engineering teams to automate data exploration, triage, and reporting.
- Proficiency in programming with Python (or R), including data manipulation, wrangling, and visualization
- Pursuing PhD in a quantitative field (e.g. Statistics, Computer Science, Mathematics, Physics, Engineering, Computational Social Science)
- Strong statistical theory foundation
- 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)
Required Skills
How to apply
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