Computer Science + Design

Listed on the application as: Interdisciplinary Computing: Retail Data Science

Use computing and retail data to drive sales

The retail industry is rapidly transforming through digitalization and is one of the largest data generators. This interdisciplinary degree bridges computer science with retail and consumer studies to meet a growing industry need for data analytics to optimize inventory, drive sales, and forecast market demand.

The program equips students with rigorous technical skills in computer science while grounding them in the dynamics of the retail industry, consumer psychology, and business strategy. With this unique combination of education, graduates of the program will be able to translate between data and strategy, ensuring that analytics truly drive innovation and performance — closing the gap between analytics and retail decision making. 

With major retailers focusing on workforce transformation, strengthening AI and data-driven roles, the demand for this talent is both immediate and expanding. 

Graduates will be well-positioned for roles such as retail data scientist, consumer insights strategist, retail technology consultant, and business intelligence leader, among other pathways at the intersection of data, technology, and retail strategy. 

What is retail data science?

Retail data science is the application of machine learning, statistical modeling, and computational algorithms to metrics such as customer transactions, e-commerce behavior, inventory levels, and supply chain operations. 

By analyzing these large volumes of interconnected and complex datasets, retail data scientists uncover trends, predict demand, optimize pricing and inventory, and personalize customer experiences, turning raw data into strategic decisions that drive business growth and innovation.

What makes this program distinctive?

Several areas of research and teaching at the University of Minnesota make the Computer Science + Retail Data Science subplan distinct from similar programs.

  • True Cross-Disciplinary Integration: Unlike a standard computer science degree or business minor, this program bridges rigorous technical computer science coursework with retail dynamics, consumer psychology, and strategic business applications.

  • Industry-Aligned Career Positioning: Our curriculum is built for students to make an immediate impact. Graduates learn to translate complex analytics into executive strategy. 

  • Hands-On Project Experience: Guided by our close industry partnerships, students engage in project-based learning and learn quickly how to apply machine learning and computational techniques directly to modern retail challenges.

Is Computer Science + Design right for me?

This subplan may be a good fit if you are interested in questions such as:

  • How do algorithms predict consumer trends and shape modern shopping experiences?
  • How can machine learning optimize supply chains, inventory and dynamic pricing in real time?
  • Why do shoppers respond to certain personalized recommendations and digital interfaces over others?
  • How can data and computational models make retail operations more sustainable and efficient?
  • How do major brands transform customer browsing and transaction data into executive business strategies?

You do not need to choose between an interest in retail and an interest in technology. This program is designed for students who want to study both—and use them together.

What can I do with this degree?

Graduates will be prepared to pursue careers and advanced study in areas including:

  • Consumer Insights Analyst
  • Merchandising Data Analyst
  • Retail Data Analyst
  • Omni-Channel Insights Analyst
  • E-commerce Data Analyst
  • Product Analyst
  • Pricing Analyst
  • Retail Media & Data Analyst 
  • Customer Analytics Analyst
  • Retail Technology Analyst

Potential employers include major national and global retailers, e-commerce platforms, consumer technology brands, retail technology startups and consulting firms, supply chain and logistics providers, and consumer analytics agencies.

Explore the curriculum

Learn more about admission requirements, required courses, and the recommended four-year plan for Interdisciplinary Computing: Retail Data Science.

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Expand your studies with the AI and Machine Learning minor

Students may also be able to complement this degree with the University of Minnesota’s new Artificial Intelligence and Machine Learning minor beginning in 2027.

The seven-course minor explores areas such as machine learning, data mining, computer vision, robotics, and natural language processing. Eligibility and course-planning requirements apply. Students interested in the minor should work with an academic advisor to determine how it can fit with their degree.

Explore the Artificial Intelligence and Machine Learning minor.