Director, Performance Analytics

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.

The Director, Performance Analytics will lead Performance Analytics, the team that owns May Mobility's core performance KPIs end to end. You will own the company's core KPIs — safety, comfort, intervention-level, system health/drop, and related performance metrics — making sure there is one accurate, reproducible, trusted number for each; own experimentation and control, deep decomposition of any KPI on request, and V&V analytics; and apply machine learning selectively where it improves analysis quality. You will partner directly with Engineering, Product, Operations, and Safety leadership to set measurement standards, define release criteria, and translate frontline operating data into the next generation of our autonomy stack. Data Engineering owns the pipeline and tooling that feeds your team; you are their primary internal customer and set their requirements.

This is a leadership role for someone who has scaled a performance analytics function inside a tech product/organization, who is comfortable making engineering and product tradeoffs alongside their team, and who sees the gap between research-grade ML and production transit-grade ML as the most interesting problem in the industry today.

Essential Responsibilities

• Set and own the Performance Analytics strategy across simulation and synthetic data to translate that strategy into a 12–24 month roadmap with measurable milestones.
• Lead, grow, and develop a team of senior performance analysts, analysts with applied ML skills, 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 deep decomposition of any KPI by geography, time, ODD element, or vehicle trend and anomaly detection
• Improves analysis quality, and continuously monitors fleet performance.
• 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; determine what data is valid to analyze and make sure conclusions hold up before they reach leadership.
• Lead team-wide quality activities including design and code reviews; hold the bar on engineering rigor for analytics, reporting, and V&V 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 in language a non-technical stakeholder can act on.
• Provide technical guidance to Engineering and Operations leaders on issue diagnosis, resolution, and the changes most likely to move our key safety and service metrics.
• Represent May Mobility's performance analytics work externally where appropriate — through publications, conference talks, partner reviews, and recruiting.

Skills and Abilities

Success in this role typically requires the following competencies:

• 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 analytics or applied-ML systems (e.g., trend/anomaly detection) 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 analytical 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, and with Data Engineering as the internal customer relationship that sets pipeline requirements without owning the pipeline; can broker disagreement between technical functions without escalation becoming the norm.
• Talent Magnet and Coach. Has personally hired and developed senior analysts 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 - including general-purpose data science support for other functions such as autonomy or release, which stays with those teams — while staying responsive to legitimate cross-functional needs.

Qualifications and Experience

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

• 8+ years of industry experience in performance/analytics, applied statistics, or data science, with at least 4 years managing senior individual contributors and front-line managers.
• Direct experience leading performance analytics, experimentation, or V&V analytics work in at least one of the following domains: autonomous vehicles or ADAS, robotics, large-scale computer vision systems, safety/performance metrics, or statistical experimentation.
• 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 and SQL; working familiarity with statistical analysis and experimentation tooling, and enough ML fluency (e.g., trend/anomaly detection) to apply it selectively within analytics workflows.
• 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.

Preferred

• Master's or PhD in Computer Science, Robotics, Statistics, EE, Mathematics, or a related quantitative field.
• Prior experience at an autonomous vehicle, robotics, or hard-tech company that has deployed products to real customers (not only research demos).
• Experience with simulation, synthetic data generation, sim-to-real transfer, or scenario-based evaluation for AV or robotics.
• Familiarity with safety-case construction, ODD definition, or regulator engagement for autonomous systems.
• Publications or conference contributions in top-tier ML, CV, or robotics venues (e.g., NeurIPS, ICML, CVPR, ICRA, RSS).
• Experience with C/C++ systems and/or GPU programming sufficient to engage credibly with onboard ML and infrastructure teams.
• Demonstrated ability to mentor and grow junior managers and senior individual contributors into bigger roles.

Physical Requirements

• Standard office working conditions which include but are not limited to prolonged sitting, standing and computer use
• Travel Required? Moderate: 11%–25% (site visits to deployment cities, partner meetings, recruiting events, and engineering offsites).

Want to learn more about our culture & benefits? Check out our website!

May Mobility is an equal opportunity employer.  All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis.   Below, you have the opportunity to share your preferred gender pronouns, gender, ethnicity, and veteran status with May Mobility to help us identify areas of improvement in our hiring and recruitment processes. Completion of these questions is entirely voluntary.  Any information you choose to provide will be kept confidential, and will not impact the hiring decision in any way. If you believe that you will need any type of accommodation, please let us know.

Note to Recruitment Agencies: May Mobility does not accept unsolicited agency resumes. Furthermore, May Mobility does not pay placement fees for candidates submitted by any agency other than its approved partners.