Senior Data Scientist, Systems Performance

Job description

Job responsibilities

• Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance.
• Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.
• Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.
• Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains…
• Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.
• Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.
• Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test…
• Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.

Job requirements

• 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.
• Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.
• Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.
• Strong Python and SQL skills, with demonstrated experience using data analysis libraries to work with large, complex datasets.
• Experience applying advanced statistical and ML methods to drive insights from large and complex data sets.
• Demonstrated experience with statistical analysis, hypothesis testing, causal analysis and data analysis.
• Demonstrated ability to work independently with minimal guidance and drive projects from problem definition through to actionable results.
• Proven communication and interpersonal skills, with the ability to explain technical findings clearly to engineering partners and leadership.