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

Build analytical models, dashboards, and data products that enable business decision-making ... Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level ...

Build analytical models, dashboards, and data products that enable business decision-making ... Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level ...

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Data Analytics Internship information

See Detroit, MI salary details

$11

$22

$41

How much do data analytics internship jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for data analytics 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 is a data analytics internship?

A Data Analytics Internship is a temporary position, often for students or recent graduates, that provides hands-on experience working with data to identify trends, create reports, and support decision-making within an organization. Interns typically assist with data collection, cleaning, analysis, and visualization, using tools like Excel, SQL, Python, or specialized analytics software. The internship offers practical exposure to real-world business problems and helps interns develop critical technical and analytical skills valuable for a future career in data analytics.

What are the key skills and qualifications needed to thrive as a data analytics intern?

To thrive as a Data Analytics Intern, you need a solid grasp of statistics, data analysis, and familiarity with programming languages like Python or R, often supported by coursework in data science or related fields. Experience with data visualization tools (such as Tableau or Power BI), SQL databases, and proficiency in Excel are commonly required. Strong problem-solving abilities, attention to detail, and effective communication skills help interns stand out in collaborative, data-driven environments. These skills are crucial for transforming data into actionable insights and supporting decision-making processes within organizations.

What types of projects do data analytics interns typically work on during their internship?

Data Analytics Interns often work on projects involving data cleaning, exploratory data analysis, and visualization to support business decisions. They may assist in creating dashboards, conducting statistical analyses, or helping to automate data collection processes. Interns frequently collaborate with data analysts, engineers, or business teams to understand project goals and contribute meaningful insights. These projects help interns gain practical experience with industry-standard tools like Excel, SQL, Python, or Tableau, while learning to communicate findings effectively within a team setting.

What is the difference between Data Analytics Internship vs Data Analyst?

AspectData Analytics InternshipData Analyst
Required CredentialsTypically pursuing or recent graduate in related fieldBachelor's or higher in data-related field, some roles prefer certifications
Work EnvironmentEntry-level, learning-focused, often part-time or temporaryFull-time, professional setting, more responsibility
Employer & Industry UsageInternships offered by companies across industries for trainingFull-time roles in various industries, more specialized
Search & Comparison IntentLooking for entry-level opportunities or internshipsSeeking full-time data analysis roles

The main difference between a Data Analytics Internship and a Data Analyst role is experience level and responsibility. Internships are designed for students or recent graduates gaining initial exposure, while Data Analysts are full-time professionals handling complex data projects. Internships serve as a stepping stone toward a full Data Analyst career.

What does a data analytics internship do?

A data analytics internship involves assisting with data collection, cleaning, and analysis to support business decision-making. Interns often use tools like Excel, SQL, or Python and gain experience in data visualization and reporting under supervision. The role provides practical skills in data analysis and understanding of industry-standard software.

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

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

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

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

What job categories do people searching Data Analytics Internship jobs in Detroit, MI look for?

The top searched job categories for Data Analytics Internship jobs in Detroit, MI are:

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

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

Infographic showing various Data Analytics 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 4 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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