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Zoox

Senior Data Scientist - Verification & Validation

Zoox is hiring a Senior Data Scientist - Verification & Validation in Foster City, United States. It pays $209k-$285k a year and Level rates it ; you can apply on Zoox.

Level's read on this job

  • Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
  • The listed pay starts 25% above the typical data scientist posting on Level.
  • Tools and skills the posting cites include Databricks.
  • Level classifies it as a senior role.
  • Level lists 228 other open roles at Zoox.

AI in this role

Databricks

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

How we rate this

Senior Data Scientist - Verification & Validation at Zoox rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Databricks

Also common in data scientist jobs at this level

Pay

This job starts at
$209k
Typical data scientist job
$167k

This posting starts 25% above the typical data scientist job. See data scientist jobs

Questions you could be asked

  1. What's a project where you used Databricks hands-on?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Databricks. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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