2027 Summer Intern, PhD, Data Science
About this role
Evaluating the safety, performance, and scalability of autonomous driving technology requires rigorous data science methods to address rare events and complex simulations. Waymo seeks a PhD Data Science intern to join teams such as Safety Eval, World Model Eval, or Simulation Data Science, working directly on core evaluation, modeling, and expansion challenges. This individual will analyze extensive on-road and simulation datasets, build statistical metrics, and translate open-ended research problems into concrete prototypes or tools that influence software development and fleet operations.
Candidates will collaborate with industry leaders and engineering groups to automate data pipelines, develop predictive features, and validate methodologies for foundation models. Successful interns combine a strong theoretical foundation in statistics with hands-on programming experience and a capacity for tackling ambiguous problems in an empirical setting.
What you will do
- Analyze large-scale on-road and simulation data to build metrics, statistical models, and predictive features that quantify safety and driving quality performance.
- Develop and enable rigorous evaluation of the Waymo Driver through a principled portfolio of assessment tools.
- Inform development work by leveraging quantitative analysis to provide early behavioral evaluation of software releases and actionable insights for expansion efforts.
- Take challenging open-ended research problems and translate them into concrete solutions or prototypes in an empirical setting.
- Develop and validate statistical and machine learning methodology to use or evaluate large-scale foundation models and draw reliable conclusions 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.
What you need
- Currently pursuing a PhD in a quantitative field such as Statistics, Computer Science, Mathematics, Physics, Engineering, or Computational Social Science.
- Proficiency in programming with Python or R, including data manipulation, wrangling, and visualization.
- Strong statistical theory foundation.
- Availability for a hybrid onsite internship position in Mountain View, CA or San Francisco, CA.
Nice to have
- Experience in machine learning applications and complex data analysis
- Familiarity with SQL, C, or C++
- Experience in processing and interpreting high dimensional data such as images and videos
- Demonstrated research capabilities through publications and understanding of statistical methodologies and foundation models
- Prior internship experience in autonomous driving or generative AI
Benefits
- Competitive compensation packages with a housing or relocation bonus if applicable
- Medical, dental, and vision insurance
- Fun intern events and networking opportunities
- Free breakfast, lunch, dinner, and snacks
- Free access to Google shuttles
- Onsite gym
Skills and tech stack
Questions candidates ask
What is the work policy for this internship?
This will be a hybrid onsite internship position based in Mountain View, CA or San Francisco, CA.
What is the compensation for this role?
The expected hourly rate for this full-time position is $85 USD, and interns are eligible for a housing or relocation bonus if applicable.
How does the application process work?
Resumes are accepted on a rolling basis until the role is filled. Candidates who want to be considered for multiple roles must apply to each one individually, up to a top three preference.
What subteams might an intern join?
Data Science interns may join subteams such as World Model Eval, Safety Eval, Tech Data Science, Safety Driving Quality Data Science, Simulation Data Science, Pre-Release Data Science, or Expansion Discovery.