Zoox

Data Scientist, Fleet Orchestration Algorithms

Zoox Foster City, California, United States · $177K–$217K/yr

Automotive · 1,001-5,000 employees

Oct 21
data-scientist Mid (2-5 yrs) Full-time United States
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About the role

Design, prototype, and help deploy algorithms for fleet vehicle assignment, staging, routing, and pricing, modeling demand and operational inputs as objectives and constraints. Collaborate with specialists to turn models into fleet decisions, evaluate their impact through simulation and experiments, and improve how orchestration changes are assessed and rolled out.

What they look for

Combinatorial Optimization Integer Optimization Stochastic Optimization Stochastic Control Reinforcement Learning Approximate Dynamic Programming Network Flows Marketplace Modeling Demand Modeling Python C++ Rust Vehicle Assignment Routing Pricing Simulation

Requirements

Requires a PhD or master's degree and at least two years of relevant industry or research experience in a related quantitative or technical field, with deep expertise in at least one specified optimization, control, reinforcement learning, network flow, or marketplace modeling area. Candidates should have strong Python, C++, or Rust coding skills, be able to formalize ambiguous problems and explain tradeoffs, and communicate and collaborate effectively.

Benefits

Paid Time Off Unpaid Time Off Stock Appreciation Rights Amazon Restricted Stock Units Health Insurance Long-Term Care Insurance Long-Term Disability Insurance Short-Term Disability Insurance Life Insurance Sign-On Bonus

Full description

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 develop the algorithms that run our robotaxi fleet: matching vehicles to riders and other missions, staging vehicles where and when they're needed, routing, and pricing.

You'll also model what goes into those decisions: rider demand, the value of the data our R&D fleet collects, servicing needs, and business inputs like events and policies. You'll be the optimization generalist on the team, working alongside specialists in marketplace economics, forecasting, and autonomy, and you'll see your algorithms run on a real autonomous fleet. You’ll join a diverse, experienced team with rapidly growing scope while working with one of the industry’s most valuable autonomous vehicle datasets.

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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

\n$177,000 - $217,000 a year

Base Salary Range

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.

Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

\nAbout 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.

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