Data Scientist, Fleet Orchestration Algorithms
Required skills
- algorithms
- vehicle assignment
- staging
- routing
- pricing
- rider demand
- data collection value
- servicing needs
- events
- policies
Nice to have
- ride-hailing
- delivery
- logistics
- AV fleets
- dispatch
- rebalancing
Role summary
Zoox is seeking a Data Scientist to develop algorithms for their robotaxi fleet, focusing on vehicle assignment, staging, routing, and pricing. This role involves modeling rider demand, data value, servicing needs, and business inputs. You will collaborate with specialists in marketplace economics, forecasting, and autonomy, and measure the impact of your algorithms on revenue, utilization, and rider experience through simulations and experiments. A PhD or MS with 2+ years of experience in a related quantitative field is required, along with deep expertise in optimization, RL, or demand modeling, and strong Python/C++/Rust coding skills. Experience in ride-hailing or AV fleets is a plus.
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.
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
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AccommodationsIf 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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