# Senior Data Scientist - Verification & Validation at Zoox

Senior Data Scientist - Verification & Validation at Zoox in Foster City, CA and 1 more. Hybrid, full-time, paying $209k–$285k. Posted March 27, 2026.

- Company: Zoox
- Location: Foster City, CA and 1 more
- Workplace: Hybrid
- Job type: Full-time
- Pay: $209k–$285k
- Posted: 2026-03-27
- Apply: https://jobs.lever.co/zoox/d856c631-446c-452f-81f5-0359b50403c9/apply
- Source: https://jobmagic.ai/jobs/senior-data-scientist-verification-validation-zoox-4jva62

## Requirements

- MS or PhD in Statistics, Computer Science, Machine Learning, Applied Mathematics, or related quantitative field
- Proficiency in Python and SQL with experience in production-quality code
- Demonstrated expertise in statistical methodologies including hypothesis testing, power analysis, spatiotemporal modeling, Bayesian inference, and multivariate analysis.
- Experience with large-scale data analysis and statistical modeling
- Proficiency with Git, unit testing, and collaborative development practices

## Description

Zoox is on an ambitious journey to develop a full-stack autonomous vehicle system for cities. We are seeking a Senior Data Scientist to join a verification and validation team that evaluates safety-critical AI systems.

You will join a team of software and data engineers that leverage methods including log data analysis, simulation, and closed-course structured testing. You'll work cross-functionally with AI software, System Design and Mission Assurance, Simulation, Sensors, and other teams to develop, execute, and iterate on validation methods and pipelines. These pipelines evaluate safety-critical systems, are highly visible, and are an important critical path element of launching our service. The ideal candidate brings a hybrid of statistical rigor and engineering mindset to drive clarity from ambiguity, establish new processes, and propel the team forward. This is a deeply technical and hands-on role where you will be expected to be a self-sufficient builder and coder, not just a manager of projects. 

### In this role, you will:

- **Design Evaluation Frameworks: **Architect statistical methodologies for safety-critical AI systems to form objective, rigorous conclusions about their performance and reliability.

- **Conduct Robust Analysis: **Deliver validation evidence to support increasingly complex operations and identify potential edge-case failures.

- **Inform Strategy:** Deliver clear, data-driven insights to development teams to guide system improvement, and to executive leadership to inform milestone-level go/no-go decisions.

- **Define Metrics:** Drive alignment across engineering teams on performance metrics and data extraction strategies.

- **Lead the Lifecycle:** Manage all phases of evaluation including prototyping, requirements capture, design, implementation, and validation.

- **Scale Pipelines:** Partner with engineers to build and maintain scalable data processing and simulation pipelines, applying distributed computing to analyze petabytes of driving data.

### Qualifications:

- MS or PhD in Statistics, Computer Science, Machine Learning, Applied Mathematics, or related quantitative field

- Proficiency in Python and SQL with experience in production-quality code

- Demonstrated expertise in statistical methodologies including hypothesis testing, power analysis, spatiotemporal modeling, Bayesian inference, and multivariate analysis.

- Experience with large-scale data analysis and statistical modeling

- Proficiency with Git, unit testing, and collaborative development practices

### Bonus Qualifications:

- Hands-on experience with production machine learning pipelines: dataset creation, training frameworks, metrics pipelines

- Experience with modern data processing technologies such as Apache Spark, Spark SQL, and Databricks

- Experience with designing metrics and delivering actionable insights that drive  business decisions