M.S. in Data Science - Residential

1 Years On Campus Masters Program

Indiana University Bloomington

Program Overview

The Master of Science in Data Science (Residential) at Indiana University Bloomington, offered through the Luddy School of Informatics, Computing, and Engineering, provides advanced training in programming, statistics, machine learning and data management. This 30-credit on-campus program combines interdisciplinary coursework, practical projects and research opportunities, preparing students to transform complex datasets into meaningful insights and pursue careers in technology, healthcare, finance, business and scientific research.

Curriculum Structure:

Year 1:

Students develop a strong foundation in statistical analysis, programming, machine learning and data management. Core coursework introduces Statistical Methods, Machine Learning, and Data Management and Engineering, helping students understand data preparation, statistical inference, computational techniques and predictive modelling. Students also begin exploring their preferred specialization through electives in applied data science, big data systems, computational and analytical methods, or managerial data science.

Year 2:

Students deepen their expertise through specialized track requirements, advanced electives and practical applications of data science. Depending on their selected track, they explore areas such as scalable data processing, statistical modelling, data visualization, business intelligence and data-driven decision-making. Students complete a capstone experience through options such as Graduate Independent Study in Data Science (DSCI-D 699), faculty-assisted research or an approved internship, allowing them to demonstrate their ability to solve real-world data challenges.

Focus Areas:

Applied Data Science, Big Data Systems, Computational and Analytical Methods, Managerial Data Science, Machine Learning, Statistical Modelling, Data Management, Data Engineering, Data Visualization, Predictive Analytics, Data Mining, Programming, Scalable Data Processing, Business Intelligence, Data Ethics and Artificial Intelligence.

Learning Outcomes:

Graduates will be able to prepare and manage complex datasets, perform exploratory data analysis and visualization, develop statistical and machine learning models, apply computational and inferential methods, implement efficient and scalable data-processing solutions, communicate analytical findings to diverse audiences and use data responsibly to solve real-world problems.

Professional Alignment (Accreditation):

The program provides interdisciplinary preparation through the Luddy School's expertise in informatics, computer science, statistics and engineering. Students gain practical experience through collaborative projects, faculty research, internships and capstone opportunities. Indiana University Bloomington holds institutional accreditation from the Higher Learning Commission (HLC). The university does not specify a separate program-specific professional accreditation for the residential Data Science master's degree.

Reputation (Employability Rankings):

97.11% Successful Career Outcomes: Data Science master's graduates from the Class of 2025 reported employment, military service or continuing education outcomes.
$93,824 Average Salary: The average reported full-time salary for the Data Science master's Class of 2025 was $93,824, based on 41 reported salaries.
347 Hiring Companies: Luddy graduate students across its master's programs were hired by 347 unique companies in the 2025 graduate outcomes report.
Leading Employers: Organizations hiring Data Science graduates include Amazon Web Services, Morgan Stanley, OpenAI and Pfizer.
In-Demand Career Roles: Graduates pursue positions such as Data Scientist, Machine Learning Engineer, Data Engineer and Generative AI Architect.

Experiential Learning (Research, Projects, Internships etc.)

At Indiana University Bloomington, the M.S. in Data Science program is designed to provide students with hands-on experience that is crucial for success in the data-driven world. Students engage in practical learning through various projects, internships, and access to state-of-the-art facilities and tools. This experiential learning approach ensures that you not only understand theoretical concepts but also apply them in real-world scenarios, preparing you for a successful career in data science.

Here are some key aspects of the experiential learning opportunities available in the program:

- Collaborative Projects: Engage in group projects that simulate real-world data challenges, allowing you to work alongside peers and faculty to solve complex problems.

- Internship Opportunities: The program encourages internships with industry partners, providing you with valuable work experience and networking opportunities in the field of data science.

- Access to Advanced Software: Students gain proficiency in essential data science tools and software, including Python, R, SQL, and Tableau, which are widely used in the industry.

- Research Laboratories: Utilize dedicated research labs equipped with the latest technology for data analysis and machine learning, fostering an environment of innovation and exploration.

- Data Science Institute: Benefit from the resources and expertise of the Indiana University Data Science Institute, which focuses on interdisciplinary research and collaboration.

- Field Trips and Workshops: Participate in field trips to local companies and workshops led by industry experts, enhancing your understanding of practical applications of data science.

- Libraries and Resources: Access extensive library resources, including databases and journals specific to data science, to support your research and learning.

Progression & Future Opportunities

Pursuing an M.S. in Data Science at Indiana University Bloomington opens the door to a wealth of career opportunities in a rapidly growing field. Graduates often find themselves in roles such as Data Scientist, Data Analyst, Machine Learning Engineer, or Business Intelligence Analyst. The demand for skilled professionals in data science continues to rise, making this program a strategic choice for your future:

- University Services: The Career Development Center offers personalized career coaching, resume workshops, and networking events specifically tailored for data science students. Additionally, the Data Science Program provides access to industry-specific job boards and internship opportunities.

- Employment Stats and Salary Figures: According to recent data, over 90% of graduates from the M.S. in Data Science program secure employment within six months of graduation, with starting salaries averaging around $85,000 per year, depending on the role and location.

- University–Industry Partnerships: Indiana University has established partnerships with leading companies such as Cummins, Eli Lilly, and Salesforce, providing students with real-world projects and internship opportunities that enhance their learning experience.

- Long-term Accreditation Value: The program is accredited by the Higher Learning Commission, ensuring that the education you receive meets high standards and is recognized by employers globally.

- Graduation Outcomes: Alumni of the program have gone on to work at top-tier companies and have reported high job satisfaction, often advancing to leadership roles within just a few years of graduation.

Further Academic Progression: After completing your M.S. in Data Science, you may choose to further your studies by pursuing a Ph.D. in Data Science or a related field, which can lead to academic positions or advanced research roles. Alternatively, you could consider specialized certifications in areas such as machine learning, artificial intelligence, or big data analytics to enhance your expertise and marketability in the job market.