Part-Time Student Worker - Data Analyst

About Zoox

Zoox is an autonomous ridehailing company building the world's first purpose-built robotaxi — fully electric, bidirectional, with no steering wheel or driver's seat. Backed by Amazon and founded to make transportation safer, cleaner, and more accessible, Zoox designs its vehicles entirely around the rider. We're currently operating in Las Vegas and San Francisco, with Austin and Miami on the horizon, and testing underway across seven U.S. markets.

About Our Part-Time Student Worker Program

Zoox's part-time student worker program puts you at the center of one of the most ambitious challenges in transportation. You'll contribute to real projects, work alongside engineers and researchers pushing the boundaries of autonomous technology, and gain experience that goes well beyond the classroom. We're looking for students who bring strong academic foundations, curiosity that doesn't stop at coursework, and a drive to be part of something that matters.

Role Overview

Analyze the coverage and exposure rate of interesting events in highway data; mind highway scenarios and build highway datasets; build dashboard to monitor highway data collection

Write Databricks notebooks to mine scenarios, create datasets, and build dashboards

Conduct exposure analysis to identity performance issues and data gaps by analyzing large-scale vehicle logs and simulation data

Write data analytic reports

Strong proficiency in SQL, PySpark, Python in production environments with standard repo practices

Experience working with time-series or sensor data

Familiarity with robotics or AV data is a plus

ML

Robotics

Currently enrolled in a B.S. or M.S. program in Computer Science, Data Science, Engineering, or a related quantitative field (or equivalent experience).

Available to commit to a minimum six month assignment.

Able to commit a minimum of 20 hours per week.

Able to work on-site at one of our office locations (Foster City).

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.