MS in Data Science
The master of science (MS) in data science program at the University of Rochester provides students with a strong background in the fundamentals and applications of data science, and is accredited by New York State.
The 30-credit STEM designated degree program is designed for students with a background in any field of science, engineering, mathematics, or business, and can be completed in two to three semesters of full-time study. We seek motivated, qualified, and well-rounded applicants. A bachelor’s degree in a STEM field is preferred but not required. Prospective students should have undergraduate mathematics experience through basic calculus, but do not need college-level statistics or data analytics. Prospective students should also have some prior programming experience. A summer bridging course will be required for admitted students who lack data structures.
We also welcome University of Rochester undergraduates to apply to our program including those who are have been part of the Hajim GEAR program. University of Rochester juniors eligible for the Early Admission Pathway (EAP) are also encouraged to apply. University of Rochester undergraduates can meet with our coordinator in their junior or senior year to discuss fitting in possible graduate courses as transfer credits.
Information Session
Watch our recorded MS Data Science information session. Upcoming information sessions will be announced in fall 2026.
Program Outcomes
Our alumni have found rewarding careers in small and large tech, healthcare, academia, research, finance, and manufacturing and services. See our program outcomes page to learn more about the career opportunities for data science graduates.
Program Components
Optional Summer Bridging Course (4 credits)
The optional summer bridging course is designed for students who matriculate without a strong computer science background. The 5-week course is offered online during late-June/early-July until early August.
Required Core Courses (16 credits)
- DSCC 440: Data Mining (fall/spring; typically taken in fall)
- DSCC 461: Introduction to Databases (formerly Database Systems) (fall/spring)
- DSCC 462: Computational Introduction to Statistics (offered fall only)
- DSCC 465: Introduction to Statistical Machine Learning (formerly Intermediate Statistical and Computational Methods) (fall/spring; typically taken in spring; prerequisites: DSCC 462 or equivalent; DSCC 440 strongly preferred)
Required Practicum (4 credits)
Practicum students work in teams of three to four to understand a sponsoring organization's business problem, clean and analyze data, and devise an appropriate solution. Students also explore ethical issues related to the use of data science, and give a final presentation to the sponsor and the class. Two faculty members from within the Goergen Institute evaluate the final presentation, which serves as the master’s degree exit exam.
- DSCC 483: Data Science Practicum (taken final semester; fall/spring)
Required Application Area Courses (minimum 10 credits)
Students must to take additional electives for a minimum of 10 credits, usually three courses, from the following application areas:
- Business and social science
- Computational methods
- Genomics
- Health and biomedical sciences
- Statistical methodology
Students have the option of exploring data science broadly across the application areas or concentrating in a single application area.
They can also substitute an independent study, independent research and/or one to two internship credits for up to six application area credits.
Optional Summer Career Development and Internship
Career Development Support
Our full-time MS program experience is supported with the assistance of staff from the ASE Office of Graduate Education and Postdoctoral Affairs and the Gwen M. Greene Center for Career Education & Connections. David Cota-Buckhout, Assistant Director of Alumni Engagement & Career, offers a FREE 0-credit 7-week fall course CASC-404: MS DSC Exploring Careers & Internship Prep to both incoming and outgoing students. Through in-class lectures and activities, self-assessments, online resources, informational interviews with alumni and industry professionals, and more, students gain skills to help them reflect strategically and align their program of study with their future career goals. In addition to the instructor, alumni from the data science MS program share their time and professional insights.
Internships
University of Rochester students are eligible for paid, summer internships through the New York State Center of Excellence in Data Science (CoE).
The CoE internship program partners with small businesses and startups in New York State to fund internship opportunities that help companies achieve their data science business objectives.
For more information, visit the CoE student internships page.
International (F-1 status) students who secure internship offers off-campus related to studies are supported with departmental academic course credit for Curricular Practical Training (CPT).