Senior Data Scientist, Autonomy Performance & Evaluation

Openkrill; United States; Hybrid; USD 149,000 - 199,000; Full time

Benefits offered by this job

Hybrid work options

Medical, dental, vision benefits

401k with company match

Job summary

Motional is seeking a Senior Data Scientist to lead evaluation methodologies for autonomous system performance. You will shape metrics, validate that changes to the autonomy stack improve safety and reliability, and partner with engineering to monitor the evaluation ecosystem.

You'll develop statistical methods for simulation and on-road data, turn edge cases into test scenarios, and mentor a team of engineers while promoting data-driven decision making across the organization.

Qualifications

• Bachelor's or higher in a quantitative field such as CS, Data Science, Robotics, Physics, or Math.
• Master's or PhD is preferred.
• Strong Python and SQL skills with experience in data analysis libraries.

Responsibilities

• Lead development of evaluation frameworks for autonomous systems using data-driven approaches.
• Collaborate with Functional Safety and Systems Engineering to align metrics with automotive standards.
• Monitor reliability of evaluation metrics and data over time to detect drift and degradation.
• Develop statistical analysis methods for simulation and on-road data.
• Turn edge cases into test scenarios and feed them back into simulation catalogs.
• Communicate findings clearly to leadership and engineering partners.
• Mentor fellow engineers and promote data-driven decision making.

Skills

Python

SQL

Data analysis

Statistical methods

ML methods

Independent work

Communication

Mentoring

Education

Bachelor's or higher in CS/CE/Data Science/Robotics/Physics/Math

Master's or PhD preferred

Tools

AWS

Distributed compute

Pandas/Numpy

Job description

Motional is seeking a Senior Data Scientist to lead evaluation methodologies for autonomous system performance. You will shape metrics, validate that changes to the autonomy stack improve safety and reliability, and partner with engineering to monitor the evaluation ecosystem.

You'll develop statistical methods for simulation and on-road data, turn edge cases into test scenarios, and mentor a team of engineers while promoting data-driven decision making across the organization.