About The Role

Role Overview

This role focuses on building a data-driven safety risk model that quantifies and improves autonomous-vehicle driving performance, along with the data analysis work that supports it. The student will work within the Safety Strategy & Operations team on a 6-month project spanning model development, empirical experimentation, and large-scale driving/simulation data analysis.

Responsibilities

Support designing, building, and iterating on a data-driven safety risk model that quantifies driving performance and surfaces safety-relevant signals across the autonomy stack
Assist developing and maintaining dataset management pipelines — curation, labeling, versioning, and quality checks — that feed the risk model and downstream analyses
Support defining and running empirical experiments that “show it with data” rather than relying on assumptions

Required Qualifications

Assist analyzing large-scale driving and simulation datasets to identify trends, edge cases, and opportunities to improve autonomy performance
Currently pursuing a B.S. or M.S. in a relevant quantitative field (Engineering, Computer Science, Statistics, Physics, or similar)
Strong programming skills in Python
Help work through ambiguous, open-ended problems with a researcher’s mindset and a bias toward rapid iteration
Solid data manipulation understanding (e.g., SQL, PySpark, Scala)
Solid foundation in statistics, machine learning, and risk or reliability modeling
Help communicate complex results, trade-offs, and uncertainty clearly to the team and stakeholders
Comfort operating independently under high uncertainty on open-ended problems

Bonus Qualifications

Excellent written and verbal communication; able to convey complexity and ambiguity clearly
Experience with safety, reliability, or risk modeling (e.g., survival analysis, Bayesian methods, causal inference)
Experience with large-scale dataset management, data pipelines, or MLOps tooling
Strong teamwork and collaboration skills
Background in autonomous vehicles, robotics, or a related quantitative discipline
Prior research experience taking ambiguous, end-to-end problems from zero to a result, independently

Program Requirements

Genuine interest in autonomous vehicles and Zoox’s mission
Currently enrolled in a B.S. or M.S. program in a relevant discipline.
Available to commit to a minimum three-month assignment.
Able to commit a minimum of 20 hours per week.
Able to work on-site at one of our office locations.
Must adhere with Zoox confidentiality requirements, including refraining from using or sharing proprietary company information outside of Zoox, such as in academic research, theses, publications, or presentations.