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Waymo

Robot type
Autonomous Vehicle
Location
San FranciscoCaliforniaUSA
Job type
Commercial Operations
Posted
Aug 28, 2026
Internship

2027 Summer Intern, MS/PhD, Quantitative UX Researcher, Growth/International Expansion

Job description

Design at Waymo is about the total experience—not just how the product looks, but how it works, how it feels, and how we make our new technology accessible, approachable, and useful for everyone. We design the intuitive, delightful experience for our riders, and we also build the powerful, complex tools used by our fleet operations teams and the engineers who build the Waymo Driver. We are a highly multidisciplinary team of UX Designers, User and Market Researchers, UX Engineers, Content Designers, Industrial Designers, CAD Designers, Studio Engineers, and Technical Artists. We dig deep to understand the attitudes, emotions, and behaviors of all our users.

Job responsibilities

  • Assist in the design, programming, and launching of surveys to potential users in London and Tokyo to understand travel behaviors, price sensitivity, feature preferences, and perceptions of autonomous vehicles.
  • Analyze survey data and publicly available datasets to identify key market segments and growth opportunities.
  • Support quantitative analysis of user feedback from early engagement programs or market simulations.
  • Conduct comparative analyses of quantitative data across London, Tokyo, and existing US markets to inform localization strategies.
  • Synthesize and visualize quantitative findings into clear reports and presentations for cross-functional partners in Product, Marketing, and Operations.

Job requirements

  • Currently enrolled in a graduate program (Master's or PhD) in Human-Computer Interaction, Psychology, Economics, Statistics, Data Science, Marketing, or a related quantitative field.
  • Strong understanding of quantitative research methods, statistical analysis, and survey design.
  • Proficiency in programming languages used for data manipulation and statistics (e.g., R, Python, SQL) to query and analyze user-level observational data.
  • Strong analytical, problem-solving, and communication skills to present quantitative data clearly to stakeholders.

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