About this opportunity
AI Chopping Block lists this Contract Student Worker - Data Scientist opportunity in foster city, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
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 Contract Student Worker Program
Zoox's contract 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
As a Data Scientist focused on forecasting, you will help Fleet Operations anticipate the resources required to scale an autonomous vehicle service across markets. You will develop forecasting and scenario-planning capabilities across fleet availability, supply, staffing, operational demand, charging, and infrastructure. Your work will inform high-impact planning decisions and create a shared, data-driven view of future operational needs.
Responsibilities
Develop forecasting models for fleet availability, supply hours, staffing, operational workload, charging demand, and infrastructure needs
Convert spreadsheet-based planning processes into reproducible, scalable, and well-documented analytical workflows
Evaluate model performance through backtesting, forecast-versus-actual reporting, and clearly defined accuracy measures
Required Qualifications
Build scenario models that help leaders understand the staffing, cost, and infrastructure implications of operational changes and market growth
Combine statistical methods, machine learning, and AI-enabled tools to improve forecasts and make model outputs easier to interpret
Prototype AI-powered decision-support tools that explain forecast drivers, identify emerging risks, and allow leaders to explore planning scenarios
Bonus Qualifications
Partner with Workforce Management, Finance, Strategy, Data Science, and operational leaders to align assumptions and establish a shared operating forecast
Currently pursuing a master’s degree in data science, statistics, computer science, operations research, industrial engineering, economics, applied mathematics, or another quantitative field
Experience with forecasting, statistical modeling, optimization, simulation, or machine learning through coursework, research, internships, or professional projects
Communicate model outputs
An AI-native technical skill set, with demonstrated experience using LLMs, coding copilots, APIs, or agent frameworks to develop analytical products or automate technical workflows
Strong understanding of model evaluation, uncertainty, explainability, and human oversight.
Program Requirements
Ability to select the right analytical approach for the problem rather than defaulting to the most complex model.
Currently enrolled in a B.S. or M.S. program in a relevant discipline.
Strong communication, problem-solving, and cross-functional collaboration skills
Available to commit to a minimum three-month assignment.
Able to commit a minimum of 20 hours per week.
Able to work on-site in Foster City CA.
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.
#J-18808-Ljbffr
Worksite address
foster city, CA, 94420, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.