Director, Data Science

Job Summary

May Mobility is entering an exciting phase of growth as we expand our autonomous transit and mobility services across the country. Founded in 2017 by a team of experienced roboticists, perception, behavior, AI, and software engineers, we operate driverless transit shuttles in real communities — not as a research demonstration, but as a daily-service product that people rely on to get to work, school, and home.

Essential Responsibilities

• Set and own the data science strategy across simulation and synthetic data, ML evaluation (perception, prediction, planning), fleet operations analytics, and the data platform that supports them; translate that strategy into a 12–24 month roadmap with measurable milestones.
• Lead, grow, and develop a team of senior data scientists, ML engineers, and front-line managers; recruit from a small expert pool, calibrate the bar, and build a hiring brand that allows May Mobility to win against AV, robotics, and AI competitors.
• Partner with Engineering, Product, Safety, and Operations leaders to define release criteria, performance metrics, and ODD-expansion gates; use data to make the business case for what we deploy, where, and when.
• Drive ML and analytics applications end-to-end: dataset curation, scenario coverage, modeling, offboard evaluation, productionization, and continuous monitoring of fleet performance in the wild.
• Establish measurement and experimentation standards across the company — including before/after analyses for stack changes, A/B-style comparisons in simulation, and statistically credible reporting on real-world incidents.
• Lead team-wide quality activities including design and code reviews; hold the bar on engineering rigor for production data science systems.
• Track and trend technical performance of the autonomy stack in the field; surface root causes, prioritize fixes with engineering, and represent fleet-data findings to executives, regulators, and partners.
• Provide technical guidance to Engineering and Operations leaders on issue diagnosis, resolution, and the ML changes most likely to move our key safety and service metrics.
• Represent May Mobility's data science work externally where appropriate — through publications, conference talks, partner reviews, and recruiting.

Skills and Abilities

• Autonomy Data Expertise. Can reason fluently about the data produced by a modern AV stack — sensor logs, perception outputs, planning traces, simulator results, and operational telemetry — and can identify which signals matter for which decisions.
• Hands-On Technical Depth. Has personally shipped production ML or analytics systems within the last 3–5 years and is credible in code review and design review with senior engineers and scientists.
• Cross-Functional Translator. Can explain a complex ML or statistical finding to engineering, product, and executive audiences; and can extract a clear analytical brief from a vague business or safety question.
• Data-Driven Decision Making. Uses fleet, simulation, and operational data to change roadmap decisions; comfortable defending a position with data and equally comfortable being wrong in front of the team when new data arrives.
• Stakeholder Alignment. Builds durable working relationships with engineering, product, safety, and operations leaders; can broker disagreement between technical functions without escalation becoming the norm.
• Talent Magnet and Coach. Has personally hired and developed senior data scientists and front-line managers; calibrates the bar, gives direct feedback, and grows people into bigger jobs.
• Prioritization Rigor. Comfortable killing work that doesn't earn its place on the roadmap; protects the team from low-leverage requests while staying responsive to legitimate cross-functional needs.

Qualifications and 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.
• Direct experience leading data science or ML work in at least one of the following domains: autonomous vehicles or ADAS, robotics, large-scale computer vision systems, simulation and synthetic data, reinforcement learning, or large-scale ML platforms.
• Demonstrated track record leading a team of 10 or more through a major delivery — for example, a production launch, a major model rollout, a regulatory milestone, or a significant ODD or product expansion.
• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Physics, Robotics, or a related quantitative field, or equivalent practical experience.
• Strong programming skills in Python; working familiarity with the production ML stack used in modern AV/robotics environments (e.g., PyTorch or TensorFlow, distributed training, dataset and feature pipelines, experiment tracking).
• Experience setting measurement and experimentation standards inside an engineering or product organization, with credible examples of metrics or evaluation frameworks the team adopted and kept using.
• Experience operating in cross-functional partnership with engineering, product, safety, and operations leaders — comfortable both defending technical positions and adjusting them in light of business or safety constraints.