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Graduate Data Science Intern Jobs in Michigan (NOW HIRING)

Rhino Tool House

Intern

Livonia, MI · On-site

This may include research, data analysis, content creation, or other project-specific activities ... graduate from a relevant academic program (e.g., business, marketing, engineering, computer science ...

Reli Group Inc

Power BI Intern

Warren, MI

$15/hr

The intern will assist in building, maintaining, and optimizing Power BI dashboards and reports ... Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics ...

Reli Group Inc

Power BI Intern

Kalamazoo, MI

$15/hr

The intern will assist in building, maintaining, and optimizing Power BI dashboards and reports ... Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics ...

Reli Group Inc

Power BI Intern

Sterling Heights, MI

$15/hr

The intern will assist in building, maintaining, and optimizing Power BI dashboards and reports ... Current junior, senior, or recent graduate in Computer Science, Data Analytics, Statistics ...

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Graduate Data Science Intern information

What does a Graduate Data Science Intern do?

A Graduate Data Science Intern assists data science teams by analyzing large datasets, developing predictive models, and supporting data-driven decision-making. They often work with programming languages like Python or R, and use tools such as SQL, Excel, and machine learning libraries. Interns contribute to real-world projects, gain hands-on experience in data analysis, and help communicate findings to stakeholders. This role serves as a bridge between academic learning and practical application in the workplace.

What types of projects do Graduate Data Science Interns typically work on, and how do these projects support their professional development?

Graduate Data Science Interns often work on real-world data analysis projects such as building predictive models, cleaning and visualizing data, or assisting with machine learning algorithm implementation. These projects are usually part of larger team initiatives and provide interns with hands-on experience using industry-standard tools and methodologies. Collaborating closely with data scientists, engineers, and business stakeholders, interns gain exposure to the end-to-end data science workflow and receive mentorship to support their growth. This experience not only enhances their technical skills but also helps them develop problem-solving and communication abilities crucial for future career advancement.

What are the key skills and qualifications needed to thrive as a Graduate Data Science Intern, and why are they important?

To thrive as a Graduate Data Science Intern, you need foundational knowledge in statistics, machine learning, and data analysis, typically supported by a degree in a quantitative field. Familiarity with programming languages like Python or R, experience with data visualization tools, and understanding of databases are often required. Strong problem-solving abilities, curiosity, and effective communication help interns collaborate and present insights clearly. These skills enable interns to extract actionable information from data and contribute value to team projects.

What is the difference between Graduate Data Science Intern vs Data Analyst Intern?

AspectGraduate Data Science InternData Analyst Intern
Required CredentialsTypically pursuing or recently completed a degree in Data Science, Statistics, or related fieldOften pursuing or recently completed a degree in Data Analysis, Business, or related field
Work EnvironmentResearch-focused, data modeling, machine learning projects, collaborative teamsData collection, cleaning, reporting, visualization tasks
Employer & Industry UsageTech companies, finance, healthcare, academiaRetail, marketing, consulting, finance

The Graduate Data Science Intern role typically involves working on machine learning models and advanced analytics, requiring a background in data science or related fields. In contrast, Data Analyst Interns focus more on data cleaning, visualization, and reporting. Both roles are entry-level, often in similar industries, but differ in technical depth and project scope.

What are popular job titles related to Graduate Data Science Intern jobs in Michigan? For Graduate Data Science Intern jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Graduate Data Science Intern jobs in Michigan look for? The top searched job categories for Graduate Data Science Intern jobs in Michigan are:
What cities in Michigan are hiring for Graduate Data Science Intern jobs? Cities in Michigan with the most Graduate Data Science Intern job openings:
Graduate Data Science Intern jobs near you
Infographic showing various Graduate Data Science Intern job openings in Michigan as of June 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 94% Physical, 3% Hybrid, and 3% Remote job distribution.

Machine Learning Engineering Intern

Mariana Minerals

Ann Arbor, MI • On-site

$25 - $35/hr

Internship

Posted 26 days ago

Job description

About Mariana Minerals
Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We're reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.
The Role
We are hiring a Machine Learning Engineering Intern to work on real, high-impact problems within our applied ML and operations team. You will contribute directly to building and improving models that influence real-world industrial systems and decision-making.
This role is designed to provide hands-on experience building and deploying machine learning solutions in production-like environments. You will work closely with engineers and domain experts to understand complex systems and apply ML techniques to improve performance, efficiency, and reliability.
What You'll Do
  • Work on a defined ML project with clear deliverables by the end of the internship
  • Build and experiment with models using Python, PyTorch/TensorFlow, or similar tools
  • Analyze real-world datasets to identify patterns, anomalies, and optimization opportunities
  • Support development of data pipelines, feature engineering, and model evaluation
  • Collaborate with engineers and domain experts to understand system behavior and constraints
  • Run experiments, validate results, and iterate based on findings
  • Document your work and present outcomes and learnings at the end of the internship

Qualification
  • Currently pursuing a degree in Computer Science, Machine Learning, Data Science, Chemical Engineering, or related field
  • Strong fundamentals in machine learning, statistics, and/or data analysis
  • Proficiency in Python and familiarity with ML frameworks (PyTorch, TensorFlow, etc.)
  • Hands-on experience through projects, coursework, or internships
  • Ability to break down problems and execute independently
  • Clear communication skills and willingness to learn in a fast-paced environment

Why Join Us?
At Mariana Minerals, you'll be part of a mission-driven team reshaping the way critical minerals are sourced and supplied globally. You'll have the autonomy to make big decisions, the tools to innovate, and a culture that values ownership, smart automation, and collaboration.
Our culture is built on three principles:
  • Extreme Ownership - We take full responsibility for outcomes, relentlessly driving toward solutions.
  • Engineer Out Requirements, then Automate - We simplify, optimize, and then automate for scale.
  • Share Your Legos - We collaborate openly, share knowledge, and empower each other to build bigger, better solutions.

Join us as we build the future of responsible mineral sourcing and supply.
Mariana is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.

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