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Data Science Training Jobs in Michigan (NOW HIRING)

The Director, Data Science will lead the team responsible for turning data generated by the fleet ... training, dataset and feature pipelines, experiment tracking). • Experience setting measurement ...

The Director, Data Science will lead the team responsible for turning the data generated by the ... training, dataset and feature pipelines, experiment tracking). • Experience setting measurement ...

FORVIA is looking for a year-round Data Science Intern for its headquarters in Auburn Hills ... Our people enjoy an average of more than 22 hours of online and in-person training within FORVIA ...

FORVIA is looking for a year-round Data Science Intern for its headquarters in Auburn Hills ... Our people enjoy an average of more than 22 hours of online and in-person training within FORVIA ...

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... training can easily find connections to. Understand stakeholders' requests and hidden issues and ...

Data Scientist

Grand Rapids, MI · On-site

$90 - $130/hr

Work with business and technical teams to support the development and integration of data science ... Training, Vehicle Purchase Supplier Discount, Company Events, Celebrations, and more! #J-18808 ...

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Data Science Training information

See Michigan salary details

$21.5K

$91.3K

$171.2K

How much do data science training jobs pay per year?

As of Aug 23, 2026, the average yearly pay for data science training in Michigan is $91,313.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,350.00 and $108,015.00 per year, depending on experience, location, and employer.

What is data science training?

A Data Science Training job involves teaching and guiding individuals or teams in data science concepts, tools, and techniques. Trainers design curricula, conduct workshops, and provide hands-on experience with programming languages like Python or R, machine learning, and data visualization. They may work for educational institutions, corporate training programs, or independently to upskill professionals. The goal is to equip learners with the skills needed to analyze data, build models, and make data-driven decisions.

What are the typical responsibilities of a professional in data science training?

Individuals in Data Science Training roles are responsible for developing, organizing, and delivering curriculum on topics such as data analysis, machine learning, and data visualization. They often lead workshops, create interactive tutorials, and provide one-on-one guidance to learners from diverse backgrounds. Collaboration with data science teams and subject matter experts to ensure training content is current and industry-relevant is common. Additionally, professionals assess learner progress and adapt materials to continuously improve the educational experience. This role is ideal for those passionate about teaching and staying at the forefront of new data science advancements.

What are the key skills and qualifications needed to thrive in data science training, and why are they important?

To excel in Data Science Training roles, you need a solid foundation in data analysis, statistical modeling, and expertise with programming languages like Python or R, often supported by a degree in data science or a related field. Familiarity with tools such as Jupyter Notebooks, SQL, machine learning platforms, and certifications like Google Data Analytics or Microsoft Certified: Data Scientist Associate are highly valued. Excellent communication, patience, and instructional skills help convey complex topics clearly and foster a collaborative learning environment. These combined skills are essential for effectively designing and delivering training that empowers learners to succeed in the rapidly evolving field of data science.

How do I get a job in data science training with no experience?

To get a job in data science training with no experience, focus on building foundational knowledge through online courses, certifications, and practical projects. Developing strong communication skills and familiarity with tools like Python, R, or SQL can also improve your chances, and gaining experience through internships or volunteering can help demonstrate your abilities to employers.

What training do you need to be a data science training?

To become a data science trainer, you typically need a strong background in data science, including skills in programming languages like Python or R, statistical analysis, and machine learning. Relevant certifications, such as Certified Data Scientist or specialized training programs, can enhance credibility, and experience with data tools and platforms is often required. Continuous learning and staying updated with industry trends are also important for effective training.

What are the most commonly searched types of Data Science Training jobs in Michigan?

The most popular types of Data Science Training jobs in Michigan are:

What are popular job titles related to Data Science Training jobs in Michigan?

For Data Science Training jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Data Science Training jobs in Michigan look for?

The top searched job categories for Data Science Training jobs in Michigan are:

Infographic showing various Data Science Training job openings in Michigan as of August 2026, with employment types broken down into 65% Full Time, 12% Part Time, 6% Temporary, and 17% Contract. Highlights an 96% In-person, and 4% Remote job distribution, with an average salary of $91,313 per year, or $43.9 per hour.

Director, Data Science

May Mobility

Ann Arbor, MI • On-site

Full-time

Re-posted 27 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.