Data Scientist – Perception Verification, Validation

• Define key performance metrics to measure the impact of new features on the perception stack and end-to-end system behavior
• Create and maintain datasets for evaluating the perception stack and end-to-end driving performance
• Analyze large-scale metric results to identify patterns and insights about perception failure modes
• Present results and insights to leadership
• Design and implement statistical methods to quantify uncertainty in performance and validation metrics
• Work closely with data scientists, perception engineers, and systems engineers
• Verify and validate the perception stack of Zoox's autonomous driving system

• Master's or PhD degree in Statistics, Mathematics, Computer Science, or a related field
• Proficiency using data query languages, including SQL and/or Spark/Scala, to build complex and efficient data queries at scale
• Proficiency using Python to build production-quality code
• Basic experience with autonomous driving, safety-critical systems, or computer vision systems
• Proficiency in exploratory data analysis (EDA) and data visualization
• Background in statistical modeling and analysis
• Experience making data-driven decisions connecting point and uncertainty estimates to business impact

Demonstrates expertise in statistical modeling, data analysis, and performance evaluation within autonomous driving systems. Proficient in utilizing data query languages and programming to derive insights and validate system performance metrics.

• Statistical Modeling
• Data Analysis
• SQL
• Python
• Exploratory Data Analysis

• Statistical Modeling
• Data Analysis
• Data Query Languages
• SQL
• Python
• Data Visualization
• Performance Metrics
• Uncertainty Quantification
• Exploratory Data Analysis
• Pattern Recognition

• Presentation Skills
• Collaboration

• Autonomous Driving
• Safety-Critical Systems
• Computer Vision

• Spark
• Scala