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 [placeholder] 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.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
