Director, Data Science
New
M
May MobilityAutonomous vehicles
Remote, USAFull-TimeDirector
Salary217,000 - 312,000 USD per year
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Job Details
- Experience
- 8+ years of industry experience in data science, machine learning, or applied research, with at least 4 years managing senior individual contributors and front-line managers.
- Required Skills
- PythonMachine LearningPyTorchData scienceTensorflowComputer Vision
Requirements
- 8+ years of industry experience in data science, machine learning, or applied research.
- At least 4 years managing senior individual contributors and front-line managers.
- Direct experience in autonomous vehicles, robotics, computer vision, simulation, reinforcement learning, or large-scale ML platforms.
- Demonstrated track record leading a team of 10 or more through a major production launch or regulatory milestone.
- Bachelor's degree in a quantitative field or equivalent practical experience.
- Strong programming skills in Python.
- Familiarity with production ML stacks (e.g., PyTorch or TensorFlow, distributed training, feature pipelines).
- Experience setting measurement and experimentation standards in an engineering organization.
- Demonstrated ability to operate in cross-functional partnerships with Engineering, Product, Safety, and Operations.
Responsibilities
- 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.
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