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Data Science Machine Learning Jobs in Michigan (NOW HIRING)

Meijer Companies Ltd

Data Scientist

Grand Rapids, MI · On-site

Build prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, data transformations, statistical models, machine learning and artificial intelligence ...

Stellantis

Data & AI SCIENTIST

Auburn Hills, MI · On-site

Build predictive models and machine-learning algorithms * Writing and refactoring the code into ... Be a specialist on specific data science fields (e.g. NLP, Computer Vision, Time Series) Basic ...

Rock Connections

Manager, Data Science

Detroit, MI · On-site

As the Manager, Data Science, you'll lead a team of data scientists as they apply data science to ... Apply statistical analysis, machine learning, and predictive modeling techniques to solve business ...

KPIT

Data and AI Lead

Novi, MI · On-site

Responsibilities : • Define and execute the Data science, machine Learning and AI-powered diagnostics roadmap for DTC/DID evolution • Transition from rule-based diagnostics → predictive and ...

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All JobsData Science Machine Learning JobsData Science Machine Learning Jobs in Michigan

Data Science Machine Learning information

See Michigan salary details

$32.7K

$107K

$171.3K

How much do data science machine learning jobs pay per year?

As of Jul 22, 2026, the average yearly pay for data science machine learning in Michigan is $106,978.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $118,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Machine Learning professional, and why are they important?

To thrive as a Data Science Machine Learning professional, you need a strong background in statistics, programming (usually Python or R), and a solid understanding of machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications such as AWS Certified Machine Learning, are typically valuable. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These skills enable professionals to develop robust models, extract actionable insights, and drive data-driven decision-making in organizations.

What are some common challenges faced when deploying machine learning models as a Data Science Machine Learning professional?

A frequent challenge in this role is bridging the gap between building accurate models in a controlled environment and deploying them effectively in production systems. Issues such as data drift, model performance degradation, and integration with existing IT infrastructure often arise. Collaboration with engineering and IT teams is crucial to ensure models are scalable, maintainable, and secure. Regular monitoring and updating of deployed models are also essential responsibilities to sustain their value to the business.

What is the difference between Data Science Machine Learning vs Data Analyst?

AspectData Science Machine LearningData Analyst
Required SkillsProgramming (Python, R), statistics, machine learning algorithmsData visualization, SQL, basic statistics
Work EnvironmentDeveloping models, coding, experimenting with algorithmsData reporting, dashboard creation, data cleaning
Industry UsageTech, finance, healthcare, where predictive models are neededBusiness intelligence, marketing, operations

Data Science Machine Learning professionals focus on building predictive models and algorithms using programming and advanced statistics, often working on complex projects. Data Analysts primarily interpret data through visualization and reporting to support business decisions. While both roles require data skills, Data Science Machine Learning involves more technical programming and modeling, whereas Data Analysts focus on data interpretation and presentation.

What is data science machine learning?

Data science machine learning refers to the use of algorithms and statistical models to analyze and draw insights from complex data sets. In this field, professionals use machine learning techniques to build predictive models, automate decision-making processes, and uncover patterns in data. Machine learning is a core component of data science, enabling systems to improve their performance over time without being explicitly programmed. Data scientists with machine learning expertise are in high demand across industries like healthcare, finance, and technology.
Data Science Machine Learning jobs near you
Infographic showing various Data Science Machine Learning job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $106,978 per year, or $51.4 per hour.
Data Scientist

Data Scientist

Meijer Companies Ltd

Grand Rapids, MI • On-site

Full-time

Posted 20 days ago

Meijer rating

6.2

Company rating: 6.2 out of 10

Based on 1,614 frontline employees who took The Breakroom Quiz

20th of 39 rated national retailers

Job description

As a family company, we serve people and communities. When you work at Meijer, you're provided with career and community opportunities centered around leadership, personal growth and development. Consider joining our family - take care of your career and your community!

Meijer Rewards

  • Weekly pay

  • Scheduling flexibility

  • Paid parental leave

  • Paid education assistance

  • Team member discount

  • Development programs for advancement and career growth

Please review the job profile below and apply today!

The Pharmacy Analytics team at Meijer leads the strategy, development and integration of analytics for Meijer Pharmacy. Data Scientists on the team will drive data wrangling, statistics, Machine Learning, Artificial Intelligence and system efficiencies by delivering innovative data driven solutions. Through these applications, data scientists drive material business value, mitigate business and operational risk, and significantly impact customer experience. This role works directly with merchandising, marketing, operations, IT, and vendor partners.


What You'll Be Doing:

  • Deliver against the overall data science strategy to drive a safe and secure patient experience, marketing, customer loyalty, and operational performance.
  • Partner with stakeholders to define requirements which meet system and customer experience needs for data science projects.
  • Partner with stakeholders to understand the journey that will be improved with the data science deliverables.
  • Build prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, data transformations, statistical models, machine learning and artificial intelligence functions to meet end user needs.
  • Partner with product development and technology teams to deploy pipelines into production environment following Safe Agile methodology as required.
  • Develop data driven solutions for strategic cross-functional initiatives, develop and present business cases, and gain stakeholder alignment of solution.
  • Help to define, document and follow best practices for ML/AI development at Meijer.
  • Deliver communication to data consumers to ensure they understand data science products, have the proper training, and are following the best practices in application of data science products.
  • Monitor and analyze Key Performance Indicators to ensure the usage, adoption, health and value of data products.
  • Partner and communicate with internal teams and IT to ensure the architecture of data and systems are meeting data science team service level needs
  • Maintain relationships with key partners, suppliers and industry associations and continue to advance data science capabilities, knowledge and impact
  • This job profile is not meant to be all inclusive of the responsibilities of this position; may perform other duties as assigned or required

What You'll Bring With You:

  • Advanced Degree (MA/MS, PhD) in Mathematics, Statistics, Economics, Sociology or related quantitative field
  • 4+ years of relevant data science experience in an applied role preferable in retail, pharmaceutical, logistics, supply chain or CPG industry.
  • Demonstrated strength in using: Python, Databricks, Azure ML, Azure Cognitive Service, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch.
  • Experience with Azure Cloud technologies: Azure Synapse, Azure Data Factory, ADLS, and Azure DevOps/MLOps
  • Experience with Microsoft Fabric, PowerBI Reporting, Semantic Models, Ontology, Copilot
  • Experience working with large datasets and developing ML/AI systems such as: natural language processing, speech/text/image recognition, supervised and unsupervised learning models, forecasting and/or econometric time series models
  • Proactive, curious and action oriented
  • Ability to collaborate with, and present to internal and external partners
  • Able to learn company systems, processes and tools, and identify opportunities to improve
  • Detail oriented and organized
  • Ability to meet production deadlines
  • Strong communications, interpersonal and organizational skills
  • Excellent written and verbal communication skills
  • Understanding of intellectual property rights, compliance and enforcement. Appreciation of HIPAA and other personal health or credit information confidentiality.

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