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Data Science Machine Learning Jobs in Michigan (NOW HIRING)

Saanvi Technologies

Machine Learning Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Machine Learning Engineering Engineer 3 Dearborn, MI W2 Position Description: We are seeking an ... This role combines expertise in Data Science, Software Engineering, and MLOps to deliver scalable ...

Corning

$95K - $130K/yr

You will help translate data science prototypes into secure, scalable, and production-ready ... end machine learning pipelines covering data ingestion, preprocessing, training, validation ...

Rocket

Manager, Data Science

Detroit, MI · On-site

... machine learning, and predictive modeling techniques to solve business problems • Support the ... data science problems • Monitor the performance of implemented solutions and conduct recurring ...

Varsity Tutors

Data Science Tutor

Ann Arbor, MI · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Detroit, MI · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Kalamazoo, MI · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

May Mobility

Director, Data Science

Ann Arbor, MI · On-site

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. • ...

May Mobility

Director, Data Science

Ann Arbor, MI · On-site

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. • ...

Delta Dental of Michigan

Data Scientist

Okemos, MI · Hybrid

Develops and implements advanced statistical models using casual modelling, machine learning and optimization techniques. * Leads the team incorporating new Data Science techniques to enhance the ...

Delta Dental of Michigan

Data Scientist

Okemos, MI · On-site

Develops and implements advanced statistical models using casual modelling, machine learning and optimization techniques. * Leads the team incorporating new Data Science techniques to enhance the ...

SwiftCruit

Data Scientist

Okemos, MI · On-site

$110 - $140/hr

Develops and implements advanced statistical models using casual modelling, machine learning and optimization techniques. * Leads the team incorporating new Data Science techniques to enhance the ...

FastTek

Machine Learning Engineer

Dearborn, MI

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer ... This role combines expertise in Data Science, Software Engineering, and MLOps to deliver scalable ...

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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 Aug 12, 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?

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 August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 12% Part Time, 1% Temporary, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $106,978 per year, or $51.4 per hour.

Research Engineer - Prognostics & Applied Data Science

HTC Global Services

Dearborn, MI • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago

Job description

Job Title
Research Engineer - Prognostics & Applied Data Science
Overview
We are seeking a Research Engineer with expertise in applied data science, machine learning, and predictive modeling to develop advanced prognostic features for connected vehicle systems. This role focuses on building predictive models, processing large-scale vehicle data, and developing algorithms that support diagnostics, fault detection, and remaining useful life estimation for vehicle components.
This is a hybrid position requiring four days per week onsite.
Key Responsibilities
  • Develop prognostic features from concept through production deployment.
  • Build physics-informed machine learning models that combine first-principles physics with machine learning techniques.
  • Design prognostics and Remaining Useful Life (RUL) models for vehicle subsystems.
  • Convert predictive models into optimized C++ code for embedded vehicle systems.
  • Develop digital signal processing pipelines and time-series analytics for multi-sensor vehicle data.
  • Design and validate fault detection and isolation (FDI) algorithms.
  • Apply statistical methods including causal inference, multivariate analysis, ANOVA, principal component analysis (PCA), clustering, neural networks, and Gaussian regression.
  • Support the complete development lifecycle from modeling and simulation through hardware validation and production deployment.
  • Collaborate with subject matter experts to develop diagnostics and prognostic algorithms for vehicle components and systems.
  • Process and analyze large-scale telemetry data using Python, SQL, Spark, Hadoop, and cloud platforms.
  • Utilize MATLAB, Simulink, and calibration tools to develop and optimize predictive algorithms.
  • Work cross-functionally to support successful implementation of production software.

Required Qualifications
  • Master's degree in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Physics, Mathematics, or a related field, or an equivalent combination of education and experience.
  • 4+ years of experience applying statistical methods such as ANOVA, PCA, correspondence analysis, clustering, factor analysis, multivariate analysis, neural networks, causal inference, and Gaussian regression.
  • 3+ years of experience with Python and SQL.
  • Experience with C++ programming.
  • Experience with data science methodologies and cloud-based data platforms.
  • Experience with embedded controls, onboard diagnostics, sensor processing, and physics-based modeling.
  • Experience using numerical modeling and simulation tools such as MATLAB and Simulink.
  • Experience with digital signal processing (DSP), data structures, algorithms, and software engineering principles.
  • Strong analytical, communication, interpersonal, and problem-solving skills.
  • Self-motivated with the ability to work in cross-functional teams.

Preferred Qualifications
  • PhD in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Physics, Mathematics, or a related field.
  • Experience in dynamic systems, controls, robotics, or prognostics and health management.
  • Experience developing automotive prognostics using connected vehicle data.
  • Experience applying machine learning methods including time-series forecasting, random forests, clustering, and neural networks.
  • Experience with Python, R, Spark, and Hadoop.
  • Experience developing embedded automotive software using MATLAB and C++.
  • Familiarity with ATI and ETAS calibration tools.
  • Excellent verbal and written communication skills.

What Makes HTC A Great Place To Build Your Future
HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies.
At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks.
Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
#LI-Hybrid #LI-CP1

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