May Mobility
Senior Data Scientist - Metrics
$163K–$240K
Ann Arbor, MI +1 · Senior · Full-time · Posted Dec 7, 2025
- Location
- Ann Arbor, MI
Ann Arbor, Michigan, United States - Experience
- 5+ years in data science, applied machine learning, robotics, or autonomous systems; 2+ years in AV, ADAS, robotics, or another safety-critical domain involving vehicle behavior analysis.
- Education
- B.S., M.S., or Ph.D. in Engineering, Data Science, Computer Science, Math, or a related quantitative field.
About the job
Develops safety and comfort metrics and models to evaluate autonomous vehicle performance, identify risky or anomalous behavior, and inform engineering decisions.
What you'll do
- Develop and refine safety and comfort metrics using real-world and simulation data; build ML and non-ML models to detect unsafe, uncomfortable, or anomalous behaviors.
- Analyze drive logs and simulation datasets to identify patterns, regressions, and system gaps, and integrate metrics into engineering workflows.
- Communicate findings and recommendations to engineering leaders and cross-functional teams.
What they ask for
- Proficiency in Python, SQL, and data analysis tools such as Pandas, NumPy, or Spark; expertise analyzing high-dimensional or time-series sensor, log, and simulation data.
- Strong understanding of vehicle dynamics, kinematics, agent interactions, and road and traffic elements.
- B.S., M.S., or Ph.D. in Engineering, Data Science, Computer Science, Math, or a related quantitative field.
- Demonstrated experience developing or evaluating safety and/or comfort metrics, and hands-on experience with real-world driving logs and/or simulation data.
Nice to have
- Background in motion planning, behavior prediction, or multi-agent interaction modeling.
- Experience designing metric-driven development, KPIs, and automated triaging pipelines.
Pay
$163,477 — $240,408 USD (base salary)
Tools
Python, SQL, Pandas, NumPy, Spark
AI focus
Build ML and non-ML models to detect unsafe, uncomfortable, or anomalous autonomous-vehicle behavior; use metrics to evaluate performance and guide product and engineering decisions.
Model-written summary · the original posting is authoritative