Description
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
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- 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.
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