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Data Science Training Jobs in Michigan (NOW HIRING)

Stellantis

Data Engineer - Supply Chain

Auburn Hills, MI · On-site

$108K - $130K/yr

Partner with data scientists and AI engineers to support model training, scoring, and deployment needs * Establish and follow best practices for data modeling, naming conventions, version control ...

Munich Re

Principal Data Scientist - FCAS

Gaylord, MI · On-site +1

... training can easily find connections to. Understand customers' requests and hidden issues and ... Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or ...

Munich Re

Principal Data Scientist - FCAS

Ann Arbor, MI · On-site +1

... training can easily find connections to. Understand customers' requests and hidden issues and ... Six (6) or more years of data science/predictive analytics experience in insurance or eight (8+) or ...

IntraEdge

AI Data Engineer

Detroit, MI

$113K - $136K/yr

Collaborate with data scientists and ML engineers to prepare, integrate, and manage large-scale datasets for model training and deployment. * Manage real-time data: Develop streaming data pipelines ...

Stellantis

Data Engineer - Supply Chain

Auburn Hills, MI

$108K - $130K/yr

Partner with data scientists and AI engineers to support model training, scoring, and deployment needs * Establish and follow best practices for data modeling, naming conventions, version control ...

University of Michigan

Data Architect Senior

Ann Arbor, MI · On-site

$65.75 - $88/hr

This is a high-ownership role for an engineer-scientist who wants to work at the boundary of ... Support distributed model training and evaluation on high-performance computing and cloud ...

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All JobsData Science Training JobsData Science Training Jobs in Michigan

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:

Data Science Training jobs near you
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.

Data Engineer - Supply Chain

Stellantis

Auburn Hills, MI • On-site

$108K - $130K/yr

Full-time

Re-posted 9 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

15th of 45 rated automakers

Job description

We are building an AI-enabled supply chain that senses, predicts, prescribes, and acts. The Data Engineer plays a critical role in enabling this vision by designing, building, and operating enterprise-grade data pipelines and analytical data products that power advanced analytics, optimization, automation, and agentic AI solutions across the Supply Chain organization.
This role focuses on production-ready data engineering-ensuring data is reliable, governed, scalable, and fit for decisioning. The Data Engineer partners closely with Data Science, AI Engineering, Automation, and Platform teams to deliver high-quality data assets embedded into operational workflows.
Responsibilities include but not limited to:
  • Design, build, and maintain scalable batch and near-real-time data pipelines supporting supply chain analytics and AI use cases
  • Ingest, transform, and curate data from enterprise and operational systems (ERP, planning, logistics, manufacturing, execution platforms)
  • Develop and maintain analytical data models and feature-ready datasets to support data science, optimization, and agentic AI workflows
  • Implement data quality validation, monitoring, and alerting to ensure trust and reliability of downstream analytics
  • Optimize data pipelines and storage for performance, cost, and scalability
  • Partner with data scientists and AI engineers to support model training, scoring, and deployment needs
  • Establish and follow best practices for data modeling, naming conventions, version control, and documentation
  • Ensure data solutions comply with enterprise standards for security, privacy, lineage, and governance
  • Support production operations, including incident investigation and root cause analysis related to data issues

Basic Qualifications:
  • Bachelor's in Computer Science, Information Systems, or a related field required
  • 8+ years of professional experience in data engineering, analytics engineering, or data platform development
  • Strong proficiency in Python and SQL for data transformation and pipeline development
  • Experience designing and maintaining production-grade data pipelines and analytical data models
  • Hands-on experience with modern data platforms such as Databricks, Spark, Snowflake, or equivalent
  • Solid understanding of data quality, validation, and monitoring concepts
  • Experience working with structured and semi-structured data at scale
  • Proven ability to own production data pipelines end-to-end (design → deployment → monitoring → incident response)
  • Demonstrated ability to operate independently, drive technical decisions, and deliver solutions in ambiguous environments with minimal oversight
  • Ability to collaborate effectively with analytics, AI, and software engineering teams

Preferred Qualifications:
  • Master's Degree
  • Experience supporting machine learning or advanced analytics pipelines, including feature engineering and model scoring data
  • Experience with orchestration tools, CI/CD, and version control for data pipelines
  • Familiarity with streaming or event-driven data architectures
  • Experience working with supply chain, operations, manufacturing, or ERP data
  • Knowledge of data governance, metadata management, and lineage tools
  • Experience supporting BI or downstream analytics tools (e.g., Power BI) and enterprise data platforms (e.g. Palantir Foundry)

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