Data & Insights Manager, May Mobility

• Strong proficiency in Python, SQL, and data analysis tools (e.g., Pandas, NumPy, Spark)
• Deep understanding of vehicle kinematics and ability to develop
• Mastery of data visualization tools to visualize complex data in a way that non-experts can interpret
• Excellent technical communication skills with the ability to clearly present complex model designs and results to both technical and non-technical stakeholders
• Detail-oriented with a focus on validation, testing, and error detection
• B.S, M.S. or Ph.D. Degree in Engineering, Data Science, Computer Science, Math, or a related quantitative field
• Minimum of 5+ years of industry experience leading or deploying data analysis systems in robotics or autonomous vehicles
• Minimum of 2+ years of specific development experience with Python, large-scale data processing, and metric design
• Demonstrated ability to identify regressions and patterns in high-dimensional or time-series sensor data
• Exceptional verbal and written communication skills for cross-team collaborations
• Strong experiences and motivation to work in fast pace startup environments with creative and critical thinking capabilities
• Strong confidence and comfort to prioritize tasks, projects and requests with good project management understanding

Desirable

• May Mobility is experiencing a period of significant growth as we expand our autonomous shuttle and mobility services nationwide
• We are seeking an experienced Manager of Data Science to lead the team responsible for developing insights from autonomous vehicle data
• In this role, you will build and guide a high-performing team of engineers as they create scalable methods to make our AV data searchable and actionable
• You will define the roadmap for data observability, enabling faster issue triage, robust test set creation, and high-quality dataset curation
• Join us to lead the strategy that powers our autonomy improvements and shapes critical business decisions
• Manage a team of data scientists to define and extract key autonomous vehicle performance metrics to validate software readiness
• Build and maintain self-serviced platforms that allow teams to query key metrics and drill-down on massive datasets
• Analyze large-scale drive logs and simulation datasets to identify patterns, regressions, and system gaps
• Collaborate with engineering leaders and cross-functional teams to translate complex statistical findings and insights into concrete action items