Masters
Part-Time or Full-Time
Fall, Spring
On-Campus
About the MS in Data Science at Loyola
Data science is a multi-disciplinary field combining techniques from mathematics, computer science, and statistics to organize, analyze, visualize, and extract useful information from data.
From business to medicine, neuroscience to sports, marketing to public policy, the explosion of huge mountains of data impacts every imaginable field. The surge of available data has multiplied the need for professionals who can understand and clearly communicate — to experts and non-experts alike — what the numbers tell us.
Whether your background is in computer science or another field, the master’s in data science will enhance your skills toolkit and allow you to gain a broader understanding of how to use these tools in practical applications, whatever your field.
Program Structure
The MS in Data Science is offered fully on campus at the Loyola Lake Shore campus; classes are held during the day and early evening. The program can be completed full-time or part-time on either the thesis or non-thesis track.
Thesis track students finish in 4 semesters while completing an original research project; the final semester of the thesis track is all research
Non-thesis track students complete the program in 3 semesters finishing with a data science capstone project
Are you a current Loyola undergrad?
This program is eligible for an Accelerated Bachelor's to Master's degree. Earn a Master’s with only one extra year of study following the completion of your undergraduate degree.
LEARN MOREWhy Choose Loyola for Your Data Science Master’s Degree?
The master’s in data science is offered in both a thesis and non-thesis track to fit your career and completion goals.
The master’s program is taught by a multidisciplinary faculty of highly-qualified experts with both academic and industry experience in data science. You will have many opportunities to interact and collaborate with faculty across disciplines on applied research projects such as applying data science tools in biology, detecting misinformation on the web, and identifying cyberbullying in social media.
The MS in Data Science is a collaboration of the Department of Mathematics and Statistics and the Department of Computer Science. A degree in data science, combining topics in statistics, math, and computer science ensures that you will develop a broad range of in-demand job skills that can be applied in many domains. While data science ranks among the top degrees for jobs in technology and STEM fields, a strong foundation in data skills has become essential in almost every occupation.
Mathematics and Statistics Department
The Department of Mathematics and Statistics offers a wide variety of degree programs designed for students with diverse career or higher educational goals. Find stories showcasing current students and graduates from the Data Science MS program and learn more about why Loyola is right for you.
Department WebsiteDepartment News and StoriesMeet the Faculty
Loyola is proud to have talented and nationally-recognized scholar-teachers as part of our diverse community of exceptional faculty, students and staff. Loyola faculty are known for their commitment to teaching, the dissemination of knowledge through innovative and interdisciplinary scholarly research, and a commitment to social justice and cura personalis, or care for the whole person. Visit the department faculty and staff directory to learn more about the teachers and mentors involved with the Data Science MS program.
FacultyData Science: Career Connections
The broad applicability of the skills you will master in this program is one of its strengths. These skills are in demand in many occupations, including STEM fields, business, medicine, journalism, marketing, and education. Our graduates work in multiple roles and many organizations, including for-profit, non-profit, education, and federal agencies.
Specific job options include:
- Data Analyst
- Data Engineer
- Machine Learning Engineer
- Data Scientist
- Data Architect
- Data and Analytics Manager
- Database Administrator
Because Loyola is a member of the Jesuit network of 27 colleges and universities nationwide, our graduates can access career advising services, resume and interviewing assistance, career fairs and events, and employment listings in our Career Services center, as well as at career centers at other U.S. Jesuit colleges and universities.
Job Outlook
The Bureau of Labor Statistics (BLS) Occupational Outlook Handbook is a good place to start exploring the job outlook and pay potential for specific careers and fields that interest you. More specifically, employment of data scientists is expected to grow 36% over a 10-year period from 2021 to 2031, a significant increase relative to other occupations.
Curriculum and Program Outcomes
While courses for the Data Science MS program may vary from semester to semester, Loyola’s extensive Academic Catalog will always house the official listing of courses, programs of study, academic policies, degree requirements, and specialization or concentration options.
Additionally, this resource will provide Data Science MS learning outcomes, showcasing the commitment to specific skills and growth graduates can expect to achieve following completion of the program.
2023-2024 Catalog
Browse Academic CatalogData Science Results and Skills
- Data analytics
- Statistical methods
- Problem-solving
- Programming in R and Python
- Machine Learning/Predictive Modeling
- Data Visualization
- Big Data Analytics
Costs, Scholarships, and Aid
Loyola University Chicago is committed to making your graduate and professional studies a reality. Our Cost & Financial Aid page can help better inform you about the costs and potential funding opportunities through scholarships, loans, and aid for graduate and professional education.
If you are a current Loyola undergraduate or recent alum, you may be eligible for a Returning Rambler discount. Learn more and see if you qualify on our Returning Rambler Scholarship page.
Tuition and Costs
The estimated tuition and fees for the Data Science MS totals $33750.00, or 30 credit hours at a cost of $1,125.00 per credit hour. Please note that tuition and fees for all of Loyola's academic programs are subject to change.
For more detailed information about tuition and fees, and a breakdown of how these costs are calculated on a yearly basis, please visit Tuition and Fees from the Office of the Bursar.
The Graduate School Scholarships
Information about funding opportunities within The Graduate School can be found on The Graduate School website.
Data Science MS Scholarships
The Data Science graduate program awards up to two graduate assistantships among applicants with complete applications submitted by February 15 and targeting a fall semester start.
Visit and Connect With Us
Take advantage of a variety of different visit opportunities to find your place in our Loyola community. Loyola offers graduate open houses, information sessions, individual appointments, open Zoom and text sessions, and a multitude of other ways to get to know us better.
Schedule an Appointment
Early in your search?
Connect with an Enrollment Advisor to help find your fit.
Already submitted an application?
Connect with an admissions team member to help you through the process.
Application Process
Application Deadlines
The available start terms and corresponding application deadlines for the Data Science MS are listed below. We encourage you to apply early as decisions may take longer during busy periods.
Fall: Rolling applications
Tuition Based Scholarships: February 15 Deadline
Spring: Rolling applications
Application Requirements
Application requirements for the Data Science MS include:
2 Letters of Recommendation
3.0 Minimum GPA
Personal Statement
International Student Requirements
Additional information regarding the application process for international students can be found on the International Student Requirements page.
Additional Details
For general information and a step-by-step guide to applying for graduate and professional study, please visit our Admission Process page.
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