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Director Data Jobs in Michigan (NOW HIRING)

The Director, Data Science will lead the team responsible for turning data generated by the fleet into insights that enhance the safety and efficiency of their autonomous services while collaborating ...

The Director, Data Science will lead the team responsible for turning the data generated by the fleet, simulation environment, and ML systems into insights that enhance the efficiency and safety of ...

The Director, Data Analytics & Artificial Intelligence is a senior leadership role within DENSO North America's IT Digital Center (ITDC), responsible for defining the enterprise wide strategy for ...

Venteon is currently seeking a Senior Director of Data Analytics & AI to lead enterprise data strategy for a global manufacturing organization. This executive-level position will drive the ...

As our Director of Data Science you will set the foundation that powers impactful data-driven insights; harnessing the power of data to shape our products with the potential to improve the lives of ...

As our Director of Data Science you will set the foundation that powers impactful data-driven insights; harnessing the power of data to shape our products with the potential to improve the lives of ...

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Director Data information

What does a Director of Data do?

A Director of Data oversees an organization's data strategy, ensuring the effective collection, management, and use of data across departments. They lead data teams, set data governance policies, and work to align data initiatives with business goals. Their role includes managing data architecture, ensuring data quality and security, and supporting data-driven decision making. Directors of Data often collaborate with executives and IT teams to drive innovation and improve business outcomes through analytics and data insights.

What is the difference between Director Data vs Data Analyst?

AspectDirector DataData Analyst
Required CredentialsBachelor's or Master’s in Data Science, Computer Science, or related field; often leadership experienceBachelor's degree in related field; certifications like Microsoft Data Analyst or Tableau often preferred
Work EnvironmentStrategic leadership, overseeing data teams, and setting data policiesData collection, analysis, reporting, and visualization tasks
Employer & Industry UsageUsed in large corporations, tech firms, and data-driven organizationsCommon across various industries including finance, marketing, and healthcare

The main difference between a Director Data and a Data Analyst lies in their scope and responsibilities. The Director Data focuses on strategic leadership, managing data teams, and setting organizational data policies. In contrast, the Data Analyst handles data collection, analysis, and reporting to support business decisions. Both roles require strong analytical skills, but the Director Data typically has more experience and a broader leadership role.

How does a Director of Data typically collaborate with other departments to drive business objectives?

A Director of Data regularly partners with teams such as marketing, product, finance, and operations to ensure data-driven decision-making across the organization. They help translate business goals into data initiatives, oversee the collection and analysis of relevant data, and present actionable insights to stakeholders. Strong cross-functional collaboration is essential, as the Director often leads data governance initiatives and aligns data strategy with company-wide objectives. This role requires both technical expertise and effective communication skills to bridge gaps between technical teams and non-technical departments.

What are the key skills and qualifications needed to thrive as a Director of Data, and why are they important?

To thrive as a Director of Data, you need deep expertise in data management, analytics, and strategy, supported by an advanced degree in a quantitative field and substantial leadership experience. Proficiency with data platforms (such as SQL, Hadoop, and cloud services), data governance frameworks, and often certifications like CDMP or cloud certifications is expected. Exceptional communication, strategic thinking, and team leadership skills distinguish top performers in this role. These skills ensure effective data-driven decision-making, alignment with business goals, and successful leadership of cross-functional data teams.
What are the most commonly searched types of Data jobs in Michigan? The most popular types of Data jobs in Michigan are:
What are popular job titles related to Director Data jobs in Michigan? For Director Data jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Director Data jobs? Cities in Michigan with the most Director Data job openings:
Infographic showing various Director Data job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 10% Part Time, 8% Contract, and 1% Nights. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution.
Director, Data Science

Director, Data Science

May Mobility

Ann Arbor, MI • On-site

Full-time

Posted 29 days ago


Job description

Job Summary:
May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. The Director, Data Science will lead the team responsible for turning data generated by the fleet into insights that enhance the safety and efficiency of their autonomous services while collaborating with various departments to set standards and translate operational data into actionable strategies.
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.
Qualifications:
Required:
• 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.
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.
Company:
May Mobility is a manufacturing firm that designs and develops autonomous technology vehicles for self-driving transportation solutions. Founded in 2017, the company is headquartered in Ann Arbor, USA, with a team of 201-500 employees. The company is currently Growth Stage.