Data Scientist - Perception Verification and Validation (Autonomous Driving)

Location: Boston, MA, United States; hybrid workplace

Salary: $167,000–$228,000 per year base salary, plus RSUs, Zoox Stock Appreciation Rights, and potentially a sign-on bonus

Company

Zoox is developing a fully autonomous vehicle fleet and the supporting mobility-as-a-service ecosystem, combining robotics, machine learning, and design for urban environments.

What you will do

• Define performance metrics to measure the impact of perception features on the perception stack and end-to-end driving behavior.
• Create and maintain datasets for evaluating perception and autonomous driving performance.
• Analyze large-scale metric results to identify perception failure modes and present insights to leadership.
• Design and implement statistical methods to quantify uncertainty in performance and validation metrics.
• Collaborate with data scientists, perception engineers, and systems engineers.

Requirements

• Master’s or PhD degree in Statistics, Mathematics, Computer Science, or a related field.
• Proficiency with SQL and/or Spark/Scala for complex data queries at scale, plus Python for production-quality code.
• Basic experience with autonomous driving, safety-critical systems, or computer vision systems.
• Proficiency in exploratory data analysis and data visualization.
• Background in statistical modeling and analysis, including connecting point and uncertainty estimates to business impact.

Nice to have

• Experience using AI tools to improve development efficiency and quality.
• Experience with experiment design, A/B testing, and parametric or non-parametric statistical comparisons.
• Experience analyzing geospatial data.

Culture & Benefits

• Hybrid work in Boston, Massachusetts.
• Paid time off, including sick leave, vacation, and bereavement leave.
• Unpaid time off and stock-based compensation through Amazon RSUs and Zoox Stock Appreciation Rights.
• Health, long-term care, disability, and life insurance.
• Accommodations are available during the application and interview process.