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Data Science Internship Jobs in Detroit, MI (NOW HIRING)

Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics ... Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level ...

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Data Science Internship information

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How much do data science internship jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for data science internship in Detroit, MI is $22.29, according to ZipRecruiter salary data. Most workers in this role earn between $17.12 and $24.28 per hour, depending on experience, location, and employer.

What types of projects or tasks can I expect to work on during a data science internship?

As a Data Science Intern, you may be involved in projects such as analyzing datasets to uncover trends, building and testing predictive models, or creating visual reports to help stakeholders understand key findings. Interns often support ongoing research, assist with data cleaning and preprocessing, and collaborate on team projects under the guidance of experienced data scientists. Depending on the company's focus, you might also contribute to deploying models or automating data pipelines. These tasks are designed to give you practical experience with real-world data challenges and help develop your technical and analytical skills.

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

To thrive as a Data Science Intern, you need a solid understanding of statistics, data analysis, and programming languages such as Python or R, often supported by progress towards a degree in a quantitative field. Familiarity with tools like SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and data visualization platforms (e.g., Tableau, Power BI) is highly valued. Strong problem-solving skills, eagerness to learn, and effective communication are essential soft skills for this role. These abilities are crucial for drawing insights from data, collaborating with technical and non-technical colleagues, and contributing meaningfully to projects.

What are the most commonly searched types of Data Science jobs in Detroit, MI?

The most popular types of Data Science jobs in Detroit, MI are:

What are popular job titles related to Data Science Internship jobs in Detroit, MI?

For Data Science Internship jobs in Detroit, MI, the most frequently searched job titles are:

What cities near Detroit, MI are hiring for Data Science Internship jobs?

Cities near Detroit, MI with the most Data Science Internship job openings:

Infographic showing various Data Science Internship job openings in Detroit, MI as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $46,339 per year, or $22.3 per hour.

Business Intelligence Data Scientist

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 5 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

Stellantis is seeking a highly skilled Business Intelligence Data Scientist to support advanced analytics within the Business Intelligence and Data Analytics team at the Headquarters & Technology Center in Auburn Hills, Michigan. This role is responsible for applying advanced analytical techniques to large and complex datasets in order to generate actionable insights that inform business decisions related to warranty, cost, quality performance, and operational effectiveness.
The Data Scientist will work with a variety of internal data sources to develop analytical solutions, perform deep exploratory analysis, and support predictive, diagnostic, and prescriptive analytics efforts. The role requires strong analytical thinking, statistical expertise, and the ability to clearly communicate findings to both technical and non-technical stakeholders.
The successful candidate will collaborate closely with Engineering, Quality, Finance, and IT partners and operate with a high degree of independence in a fast-paced, data-driven environment.
Key Responsibilities:
  • Analyze large, complex datasets to identify trends, relationships, risks, and opportunities related to warranty and quality performance
  • Develop and apply advanced statistical, analytical, and data science techniques to support business problem-solving and decision-making
  • Perform exploratory data analysis and root-cause investigations to explain performance drivers and anomalies
  • Design, develop, and maintain robust analytical models, metrics, and methodologies
  • Translate complex analytical results into clear insights, recommendations, and visualizations for stakeholders
  • Partner with cross-functional teams to understand business needs and deliver analytical solutions
  • Ensure analytical outputs are accurate, repeatable, and well-documented
  • Support continuous improvement of analytics processes, tools, and data usage practices
  • Contribute to the development of standardized reporting, metrics, and best practices across the organization

Basic Qualifications:
  • Bachelor's degree in a quantitative discipline such as Data Science, Statistics, Computer Science, Applied Mathematics, or a related field
  • Relevant internship experience
  • Demonstrated ability to communicate analytical findings clearly to technical and non-technical audiences
  • Excellent problem-solving, organizational, and time-management skills
  • Ability to work independently with minimal supervision

Preferred Qualifications:
  • Master's degree in a quantitative discipline
  • Experience applying predictive, diagnostic, or prescriptive analytics techniques in a business environment
  • Familiarity with data visualization and business intelligence tools (e.g., Power BI, Tableau)
  • Experience working in automotive, manufacturing, quality, or operational analytics environments
  • Experience with working across multiple deployment environments including cloud, on-premises and hybrid, using multiple operating systems
  • Experience translating complex data into clear narratives for leadership decision-making

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