Data Scientist Intern [Summer 2027]

Zoox
Foster City, CA
HybridCareer-pivot friendly

In the 12 months to 30 Jun 2026, Zoox filed 1 H-1B position titled "Senior Data Scientist". Source: U.S. Department of Labor, LCA disclosure data. A record of filings already made, not a commitment to sponsor.

Who this role is best for

Strong fit for candidates with advanced quantitative degrees who apply statistical and machine learning methods to safety-critical systems.

Best fit for

  • Candidates with a Ph.D. or Master's in Statistics or related fields and a focus on rare-event modeling
    — “Currently pursuing a Master's or Ph.D. in Statistics, Data Science, Machine Learning, Computer Science, or a related quantitative engineering/scientific discipline.”
  • Those who can translate complex statistical findings into actionable mission assurance decisions
    — “Collaborate with systems engineers and safety leads to translate complex quantitative models into rigorous mission assurance decisions.”

Things to consider

  • Must be able to relocate to the Bay Area for a full-time 12-week commitment
    — “Able to commit to a full-time, 12-week internship beginning in May/June 2027.”
  • Cannot use proprietary information from the internship in university-related work
    — “Interns at Zoox may not use any proprietary information they are working on as part of their thesis, any published work with their university, or to be distributed to anyone outside of Zoox.”

How to stand out

  • Highlight experience with Bayesian inference and spatial-temporal modeling in your resume and interview
    — “Experience or coursework in spatial statistics, space-time models, point process models, or causal inference.”
  • Showcase your ability to work with large-scale data tools like Spark or Databricks
    — “Experience querying, pipeline-building, and modeling massive datasets using Spark, Databricks, or cloud platforms.”
  • Demonstrate your ability to break down ambiguous problems into structured statistical approaches
    — “Demonstrated ability to break down ambiguous operational or system questions into structured statistical problems.”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Developed statistical and machine learning models for safety and risk assessment
  • Processed and analyzed large-scale datasets for actionable insights
  • Collaborated with systems engineers and safety leads on mission assurance decisions
Typical background
Master's or Ph.D. in Statistics, Data Science, Machine Learning, Computer Science, or related quantitative engineering/scientific disciplineExperience with statistical methods and machine learningExperience with data manipulation and querying

Skills & requirements

Required

Statistical MethodsMachine LearningData AnalysisSQLPythonDistributed Data FrameworksStatistical ModelingMachine Learning ModelingData ManipulationData QueryingCommunicationProblem SolvingSafety MetricsQuantitative Risk AssessmentSystem Performance EvaluationRare Safety Events AnalysisStatistical BaselinesOperational Risk AnalysisVehicle Behavior AnalysisSafety-critical Metrics Evaluation

Preferred

Large-scale Data ProcessingRare-event ModelingAutonomous VehiclesTransportation Network Companies

Stack & domain

PythonSQLSparkDatabricksRCommunicationProblem-solvingAutonomous VehiclesMachine LearningStatistics

About the role

Original posting from Zoox via Lever

About Our Internship Program

Zoox’s internship program offers hands-on experience with cutting-edge technology, mentorship from some of the industry's brightest minds, and the opportunity to make meaningful contributions to real projects. We seek interns who demonstrate strong academic performance, engagement beyond the classroom, intellectual curiosity, and a genuine interest in Zoox's mission to create autonomous mobility from the ground up.

Job Description

As an intern in the Quantitative Risk Assessment (QRA) team within System Design & Mission Assurance, you will apply rigorous statistical methods and machine learning techniques to quantify safety and risk across our autonomous driving systems. You will work with complex, real-world fleet and simulation datasets to model rare safety events, establish statistical baselines, and develop metrics that validate the safety and mission assurance of our purpose-built robotaxi.

In this Role, You Will…:

  • Formulate and build statistical and machine learning models to evaluate system performance and analyze rare, high-consequence safety events.
  • Process and analyze large-scale datasets using SQL, Python, or distributed data frameworks (Spark/Databricks) to extract actionable insights on vehicle behavior and operational risk.
  • Apply advanced statistical methods (e.g., Poisson processes, GLMs, Bayesian inference, point process models, or spatial-temporal modeling) to evaluate safety-critical metrics.
  • Collaborate with systems engineers and safety leads to translate complex quantitative models into rigorous mission assurance decisions.

Internship Requirements:

  • Currently pursuing a Master's or Ph.D. in Statistics, Data Science, Machine Learning, Computer Science, or a related quantitative engineering/scientific discipline.
  • Enrolled in good academic standing at an accredited college or university throughout the internship.
  • Expected to graduate between Fall 2027 and Summer 2028.
  • Able to commit to a full-time, 12-week internship beginning in May/June 2027.
  • Ability to relocate to the Bay Area, California, for the duration of the internship.
  • Interns at Zoox may not use any proprietary information they are working on as part of their thesis, any published work with their university, or to be distributed to anyone outside of Zoox.

Qualifications:

  • Statistical Foundations: Deep understanding of probability theory, regression, Generalized Linear Models (GLMs), hypothesis testing, and Bayesian methods. Experience or coursework in spatial statistics, space-time models, point process models, or causal inference.
  • Machine Learning & Modeling: Strong fundamentals in statistical modeling and ML (supervised and unsupervised learning, model validation, and metric evaluation).
  • Data Manipulation & Querying: Proficiency with basic-to-intermediate SQL and Python for data querying, data cleaning, and statistical modeling (or alternative data packages such as Spark, dplyr, or R).
  • Communication & Problem Solving: Demonstrated ability to break down ambiguous operational or system questions into structured statistical problems and clearly communicate complex quantitative findings to technical stakeholders.

Bonus Qualifications:

  • Large-Scale Data Processing: Experience querying, pipeline-building, and modeling massive datasets using Spark, Databricks, or cloud platforms.
  • Rare-Event Modeling & Domain Experience: Familiarity with autonomous vehicles, transportation network companies (TNCs), quantitative safety/risk modeling, or fraud/rare-event detection.
  • AI-Assisted Workflow & Tooling: Experience utilizing AI-assisted data analysis, modern coding agents, or LLM-driven research workflows to accelerate data exploration and model development.

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.

Follow us on LinkedIn

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.

Source: Zoox careers (Lever)

Similar roles

More roles at Zoox