MS in Data Science

Career prospects: A wealth of opportunities

Coursework in machine learning, data mining, artificial intelligence, and visualization will prepare you to capture, process, model, analyze and visualize data to make strategic business decisions to optimize outcomes. Our graduates find success in a wide range of careers, including:

• Data scientist at Athena Health
• Data scientist at BNY Mellon
• Machine learning engineer at Spotify
• Machine learning engineer at Quantiphi
• Software engineer at Amazon Web Services

Co-ops and internships: Rated #1

You’ll have opportunities to participate in co-ops and internships, ranked #1 in the country by U.S. News & World Report, that will enrich your coursework and elevate your expertise through hands-on experience. Co-op and internship positions include:

• Data science intern
• Analytics and insights co-op
• Data science/machine learning co-op
• Data and analytics intern
• Data engineering intern

Research opportunities: Pursue your passion

You’ll collaborate with world-class researchers in state-of-the-art facilities to enhance your education, advance your career prospects, and make discoveries that will change the world. Whether you’re interested in a research career, applying to PhD programs, or simply gaining more firsthand experience in the field, our wide variety of research projects will empower you to make meaningful contributions.

Interdisciplinary approach

Our interdisciplinary approach with the College of Engineering provides extensive exposure to the field and a wide range of elective courses tailored to your interests. With diverse co-op, research, and internship opportunities, you’ll gain valuable real-world experience to prepare for a successful career in our increasingly data-driven world.

Learning outcomes

An MSDS degree enables you to manage, process, analyze, and visualize data at scale. You will learn about the limitations of machine learning and data mining methods as applied to real-world problems and communicate the advantages and disadvantages of the methods to non-data experts.

You will carry out the full data analysis workflow, including unsupervised class discovery, supervised class comparison, and supervised class prediction. You will learn how to properly summarize, interpret, and communicate the analysis of results.

In this program, you will develop methods for modeling, analyzing, and reasoning about data arising in application domains such as social science, health informatics, web and social media, climate informatics, urban informatics, geographical information systems, business analytics, bioinformatics, complex networks, public health, and game design.