Data Scientist, Fleet Orchestration Algorithms
Zoox
Foster City, CA · $177k–$217k a year · Posted October 21, 2026
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Pay compared with the market
This listing pays about $197,000 a year. Across 235 open data scientist listings that state pay, the middle half runs $127,000 to $187,500 and the median is $156,500. That is 26% above the median, above the middle half of those listings.
Listed pay is what employers advertise, not what people are paid.
About the job
The Core Data Science team builds the products and data assets that let teams across Zoox measure and improve the autonomy and operational performance of our fleet. In this role, you'll focus on fleet simulation — the environment our data teams use to develop, test, and evaluate the algorithms that orchestrate our autonomous fleet (dispatch, routing, and vehicle assignment) and to understand how those algorithms perform before they reach the road.
You’ll piece together the constituent components into a coherent, easy-to-use simulation environment, filling in the gaps, and building generalizable mechanisms so data scientists can measure their algorithm's impact on fleet efficiency. You'll join a diverse, experienced team with rapidly growing scope while working with one of the industry's most valuable autonomous vehicle datasets.
In this role, you will:
Design, prototype, and help deploy algorithms for vehicle assignment, staging, routing, and pricing
Model the inputs to orchestration (rider demand, data-collection value, servicing needs, events, and policies) as objectives and constraints
Work with specialists in marketplace economics, forecasting, and autonomy to turn their models into decisions the fleet acts on
Measure impact on revenue, utilization, and rider experience through simulation, offline evaluation, and online experiments
Contribute to how we evaluate and roll out orchestration improvements
Qualifications
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/integer optimization, stochastic optimization or control, reinforcement learning/approximate DP, network flows, or marketplace/demand modeling, plus the curiosity to work across the rest
Strong coding skills in Python, C++, or Rust; you write clean, tested, version-controlled code
Ability to turn ambiguous real-world problems into well-defined models and explain the tradeoffs to non-specialists
Good communication and collaboration skills
Bonus Qualifications
Internship or research experience in ride-hailing, delivery, logistics, or AV fleets (dispatch, routing, rebalancing, pricing)
Algorithms deployed in production or used on real operational data
Publications in operations research, transportation, or robotics venues
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 accommodations@zoox.com 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.