Autonomous Vehicle Metrics and Evaluation Data Scientist - Analytics

About the Team

Our team is dedicated to advancing the future of autonomous driving technology by developing the metrics and evaluation frameworks that ensure the safety, performance, and readiness of self-driving systems. We work closely with engineering teams to analyze real-world and simulated driving data, enabling data-driven decisions that accelerate the commercialization of autonomous vehicles. Our work directly impacts critical questions such as: ‘How well does the vehicle handle complex intersections? Does it provide a passenger-safe experience during maneuvers? How do we statistically validate readiness for urban deployment?’

About the Role

We are seeking a skilled Data Scientist to join our team and play a pivotal role in defining and evaluating the performance of autonomous vehicle systems. You will design and implement quantitative metrics to assess driving behavior, safety compliance, and passenger comfort. Your work will involve analyzing large datasets, applying statistical methods, and collaborating with cross-functional teams to ensure our self-driving systems meet the highest standards of safety and reliability. This role offers the opportunity to make a significant impact on the future of autonomous driving technology.

What You'll Do

• Analyze data from real-world and simulated autonomous vehicle experiments to evaluate system performance.
• Develop and refine quantitative metrics (both rule-based and ML-driven) to assess driving behavior, safety, and passenger comfort.
• Apply statistical inference and hypothesis testing to validate the sensitivity and reliability of metrics.
• Collaborate with autonomy software, simulation, and safety teams to prioritize improvements based on data-driven insights.
• Build scalable data pipelines to automate metric computation and reporting.
• Review driving logs and participate in test rides to ground analyses in real-world performance.

What You'll Need

• 2+ years of experience in data science, applied statistics, or metrics development.
• Proficiency in Python and SQL for data analysis.
• Strong background in statistical methods (e.g., A/B testing, confidence intervals, regression).
• Experience designing metrics to evaluate complex systems (e.g., robotics, autonomous systems, or large-scale software).
• Ability to communicate technical findings to cross-functional stakeholders.

Nice to Have

• Experience with machine learning (e.g., model evaluation, feature engineering).
• Familiarity with big data tools (Spark, Hadoop, MapReduce).
• Knowledge of traffic regulations or automotive safety standards (e.g., NHTSA).