2027 Summer Intern, MS/PhD, Data Science - Commercialization Testing

You will:

• Develop, implement, and refine Bayesian forecasting models to interpret small-sample test results.
• Build and optimize predictive analytics models to monitor fleet operations and analyze vehicle behavior.
• Collaborate with Test Engineers to design experimental procedures on closed courses and simulation environments.
• Extract, process, and analyze large-scale, high-dimensional datasets from vehicle logs and depot operations using Python and SQL.
• Partner with Systems Engineering, Software Engineering, and Product teams to determine key performance characteristics for model coverage.

You have:

• Enrolled in a graduate program (Master's or PhD) in Data Science, Statistics, Operations Research, Civil Engineering (with a focus on traffic/mobility analytics), or a highly quantitative field.
• Strong foundation in predictive analytics, Bayesian modeling, and statistical inference.
• Proficiency in writing production-quality Python.
• Strong SQL skills with experience querying and synthesizing data from large-scale databases.
• Strong communication skills to present complex quantitative results and statistical limitations clearly to non-technical stakeholders.

We prefer:

• Academic coursework or research experience in traffic flow theory, intelligent transportation systems, fleet routing, or urban mobility.
• Familiarity with autonomous vehicle technology, simulation-based testing (SIL/HIL), or systems engineering principles.
• Experience with survival analysis, probability modeling, or extreme value theory applied to safety-critical systems.
• Comfort navigating highly ambiguous, unstructured problems in a fast-paced R&D environment.

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.