Staff Data Scientist Verification & Validation
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Job Location:
Boston, NH - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Zoox is on an ambitious journey to develop a full-stack autonomous vehicle system for cities. We are seeking a Staff 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. Youll 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.
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
Required Experience:
Staff IC
Key Skills
About Company
We’re reinventing personal transportation—making the future safer, cleaner, and more enjoyable for everyone. This is on-demand autonomous ride-hailing.
