- Set and own the data science strategy across simulation, synthetic data, ML evaluation, fleet operations analytics, and data infrastructure.
- Lead, grow, and develop a team of senior data scientists, ML engineers, and front-line managers.
- Partner with Engineering, Product, Safety, and Operations leaders to define release criteria, performance metrics, and ODD-expansion gates.
- Drive ML and analytics applications end-to-end from dataset curation and scenario coverage to productionization and fleet monitoring.
- Establish company-wide measurement and experimentation standards including A/B testing in simulation and statistical reporting on real-world incidents.
- Lead team-wide quality activities including design and code reviews to maintain engineering rigor.
- Track and trend technical autonomy stack performance in the field and prioritize fixes with engineering.
PythonMachine LearningPyTorch+3 more