Data Scientist, Fleet Orchestration Algorithms

Location: Foster City, CA, United States; on-site

Company

Zoox develops autonomous vehicle and robotaxi technology, including products and data assets for measuring and improving fleet autonomy and operational performance.

What you will do

• Design, prototype, and help deploy algorithms for vehicle assignment, staging, routing, and pricing.
• Model rider demand, data-collection value, servicing needs, events, and policies as objectives and constraints.
• Work with marketplace economics, forecasting, and autonomy specialists to turn models into fleet decisions.
• Measure impact on revenue, utilization, and rider experience through simulation, offline evaluation, and online experiments.
• Contribute to the evaluation and rollout of orchestration improvements.

Requirements

• PhD or MS with 2+ years of relevant industry or research experience in operations research, robotics, controls, transportation, computer science, applied math, or a related field.
• Deep expertise in at least one of combinatorial or integer optimization, stochastic optimization or control, reinforcement learning or approximate dynamic programming, network flows, or marketplace and demand modeling, plus curiosity to work across the other areas.
• Strong coding skills in Python, C++, or Rust, including clean, tested, version-controlled code.
• Ability to turn ambiguous real-world problems into well-defined models and explain trade-offs to non-specialists.
• Good communication and collaboration skills.

Nice to have

• Internship or research experience in ride-hailing, delivery, logistics, or autonomous vehicle fleets, including dispatch, routing, rebalancing, or pricing.
• Algorithms deployed in production or used with real operational data.
• Publications in operations research, transportation, or robotics venues.

Culture & Benefits

• Work with a diverse, experienced team and a rapidly growing scope.
• Use a large autonomous vehicle dataset and see algorithms run on a real autonomous fleet.