Autonomous Vehicle Metrics Scientist - Evaluation & Impact

Avride Inc.; Austin (TX); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Equal opportunity employer

Job summary

Avride Inc. in Austin, Texas is seeking a data scientist to define and evaluate metrics for autonomous vehicle systems.

You will design quantitative measures of driving behavior, safety compliance, and passenger comfort, and analyze large real-world and simulated datasets. The role involves statistical methods, ML-driven metric design, and collaboration with engineering teams to ensure safety and reliability of self-driving technology.

Qualifications

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

Responsibilities

• Analyze real-world and simulated AV data to evaluate system performance.
• Develop and refine quantitative metrics for driving behavior, safety, and passenger comfort.
• Apply statistical inference to validate metric sensitivity and reliability.
• Collaborate with autonomy software, simulation, and safety teams to prioritize improvements.
• Build scalable data pipelines to automate metric computation and reporting.
• Review logs and participate in test rides to ground analyses in real-world performance.

Skills

Python

SQL

Statistics

Metrics design

Communication

Tools

Spark

Hadoop

MapReduce

Job description

Avride Inc. in Austin, Texas is seeking a data scientist to define and evaluate metrics for autonomous vehicle systems.

You will design quantitative measures of driving behavior, safety compliance, and passenger comfort, and analyze large real-world and simulated datasets. The role involves statistical methods, ML-driven metric design, and collaboration with engineering teams to ensure safety and reliability of self-driving technology.