🕒 2 days ago
Lead product data science initiatives by building production machine-learning models, designing experiments, and translating analytics into product decisions and measurable business outcomes.
Senior Data Scientist - Verification & Validation
📅 Mar 27
PythonSQLStatistical AnalysisHypothesis Testing
📜 Description
- Design statistical evaluation frameworks to assess safety-critical AI performance and reliability.
- Analyze validation data to identify edge-case failures and support increasingly complex operations.
- Deliver data-driven insights to engineering teams and executive leadership to guide improvements and go/no-go decisions.
- Align engineering teams on performance metrics and data extraction strategies.
- Lead evaluation from prototyping and requirements capture through design, implementation, and validation.
- Build and maintain scalable data-processing and simulation pipelines with engineers, using distributed computing to analyze petabytes of driving data.
🛠️ 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
- 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
Full job 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:
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
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