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Data science students

Data Science

The master's degree program in data science prepares you for leadership positions in data analytics, information management, and knowledge engineering. It is jointly offered by the departments of Computer Science in Engineering and Mathematics in Arts & Sciences.

With a master's degree in data science, you will:

  • develop skills in computer programming, statistics, data mining, machine learning, data analysis, and visualization
  • be prepared to solve challenging problems involving large, diverse data sets from different application domains

You will explore the rapidly emerging fields of data analytics and discovery informatics—which integrates mathematics and computer science for the quantification and manipulation of information from a cognate area of application (such as science, engineering, business, sociology, healthcare, planning).

The program emphasizes:

  • strong foundations in information theory, mathematics, and computer science
  • current methodologies and tools to enable data-driven discovery, problem solving, and decision-making

Enhance your skills, advance your career

The program is designed for:

  • professionals and organizational leaders who want to take on greater IT responsibilities
  • individuals who aspire to careers using computer information science to support decision-making
  • students who want to learn technological and analysis tools used by leading science, engineering, business, academic, government, and social organizations

Data science MS mean starting salary:

NACE Data Collection of Class of 2022 Graduate Alumni


Research in data science unlocks mysteries of the galaxy

Professors Scott Field, Vijay Varma, and their students have emerged as leaders at the forefront of gravitational wave science. Merging UMass Dartmouth's mathematics, data science, and physics departments, the research consortium is one of the largest in the world.

The MS in Data Science aims to:

  • meet the growing demand for high-level information systems/science skills
  • provide a path for individuals from diverse fields to rapidly transition to data science careers
  • enable established IT and computing professionals to upgrade technical management and development skills
  • prepare graduates to apply data science techniques for knowledge discovery and dissemination to assist researchers or decision-makers in achieving organizational objectives
  • create innovators, entrepreneurs, and business professionals who will lead the development of next generation information systems

At the time of graduation, students will:

  • be able to apply contemporary techniques for managing, mining, and analyzing big data across multiple disciplines
  • be able to use computation and computational thinking to gain new knowledge and to solve real-world problems of high complexity
  • be able to communicate ideas and findings persuasively in written, oral, and visual form and to work in a diverse team environment
  • apply advanced knowledge of computing and information systems applications to areas such as networking, database, security and privacy, and web technologies
  • be prepared for career advancement in all areas of information science and technology
  • be committed to continuous learning about emerging and innovative methods, technologies, and new ideas—and be able to use them to help others
  • appreciate the professional, societal, and ethical considerations of data collection and use

The program prepares you for careers that require data analysis and representation, and a broad, flexible understanding of informatics.

The MS in Data Science is a 30-credit program. You will arrange an individual graduate program with your advisor during the first semester, subject to approval by your Graduate Committee.

All students complete 3 required computer science courses and a master’s project course. Elective courses round out the program.

Degree Requirements: MS in Data Science

Hands-on learning is crucial. You will have opportunities to:

  • participate in faculty-led projects
  • collaborate on industry, agency, and faculty-sponsored projects
  • pursue your own research interests

Faculty research is centered on data science across the disciplines: to treat disease, monitor neonate health, explore the universe, predict ocean turbulence, and solve complex numerical equations.

UMassD advantages

Bridge Program: For students who are not yet ready for the master of science degree program in data science, UMass Dartmouth offers a preparatory bridge program consisting of five courses in data science fundamentals. Offered through UMassD's Online & Continuing Education Programs, the preparatory curriculum is comprised of both online and in-person courses and may be completed within one year. Learn more

3+2 Program with Salve Regina University: UMass Dartmouth has partnered with Salve Regina University to develop a pathway for Salve Regina students to earn a bachelor’s degree in mathematics from their home school and a master’s degree in data science from UMass Dartmouth in just five years. Learn more.

Center for Scientific Computing and Visualization Research (CSCVR): An interdisciplinary center where faculty and students collaborate using high-performance computers to address mathematical, engineering, physics, biology, chemistry, and oceanography computational issues and questions. Learn more about the CSCVR

International (F-1) students who receive science, technology, engineering, and mathematics (STEM) degrees may be eligible to apply for a 24-month extension of their post-completion optional practical training (OPT). To learn about the eligibility criteria and detailed steps to apply, please review the International Student & Scholar Center (ISSC) OPT page and USCIS resources. F-1 students must consult with the ISSC to apply for STEM OPT.

University requirements for graduate admissions

  • Submit an application via the online portal. Be sure to provide your full legal name and to capitalize the first letter of all proper nouns.
  • Pay non-refundable $60 application fee (American Express, Discover, MasterCard or Visa) via the online portal. For Nursing applicants, the non-refundable application fee is $75.
  • Statement of Purpose, minimum 300 words. Unless otherwise indicated in the program requirement details, indicate your graduate study objectives, research interests and experience, and business or industry experience if applicable. If you are applying for a teaching or research assistantship, include any special skills or experience that would assist us in making assistantship decisions.
  • Resume
  • Transcripts for all post-secondary institutions attended (regardless of whether a credential is earned or not). Unofficial transcripts are accepted for admissions application review, once enrolled a final official transcript is required. International students applying with an transcript evaluation, please submit that document with your unofficial transcripts. International applicants for Data Science must submit semester-by-semester transcripts as well as consolidated transcripts. 
  • Many programs have specific recommendations/requirements, please see the additional program-specific requirements for more information.
  • International students: official TOEFL iBT, IELTS, Pearson PTE or Duolingo (if accepted by program) score. Unofficial scores are accepted for admissions application review, once enrolled official scores are required and must be sent by the testing agency (copies/scans not accepted). This is required of any applicant who did not earn a bachelor’s degree or higher degree from an accredited academic institution in the U.S. or accepted English-speaking country, see exemptions for more details. We require an overall/total minimum score of 72 on the TOEFL iBT or BAND 6.0 on the IELTS or a 52 on the Pearsons PTE Academic for entrance to any program and a minimum score of 79 on the TOEFL iBT or BAND 6.5 on the IELTS for consideration for a teaching assistantship. Some programs require higher minimum scores (see program-specific requirements). Most programs also accept the Duolingo with a minimum score of 95. The following programs do not accept the Duolingo: Art Education, Biology/Marine Biology, Nursing (MS, DNP, PhD), Psychology: Clinical, and Public Policy. 
  • All official documents are required for enrollment, please have documents (ie. test scores) sent prior to the expiration. 

Program-specific requirements

The MS in Data Science is designed for individuals with career backgrounds or undergraduate degrees in business, engineering, computer science, physical/life/social sciences, mathematics, the liberal arts, and education who want to enhance their data analytics and information science skills and credentials.

Candidates must submit the required application materials, university requirements and program-specific requirements, for consideration.


  • GRE is recommended but not required.
  • 1 letter of recommendation: from a person in the field of your academic major at the institution most recently attended or from supervisors familiar with your recent job performance. BS/MS applicants are encouraged to include a recommendation from a department faculty member willing to advise their graduate research. Applicants will be required to provide the recommenders name and email address so we can contact the recommender for the letter of recommendation.

Program deadlines

Data Science faculty

Adam Hausknecht
Adam Hausknecht, PhD
Alfa Heryudono
Alfa Heryudono, PhD
Bo Dong
Bo Dong, PhD
Cheng Wang
Cheng Wang, PhD
Donghui Yan
Donghui Yan, PhD
Sheryl Sears
Sheryl Sears
Firas Khatib
Firas Khatib, PhD
Gary Davis
Gary Davis, PhD
Hua Fang
Hua Fang, PhD
Photograph of Haiping Xu
Haiping Xu, PhD
Iren Todorova Valova
Iren Valova, PhD
Ming Shao
Ming Shao, PhD
Ming Shao
Ming Shao, PhD
Ramprasad Balasubramanian
Ramprasad Balasubramanian, PhD
Scott Field, PhD
Sigal Gottlieb
Sigal Gottlieb, PhD
Saeja Kim
Saeja Kim, PhD
Vijay Varma
Vijay Varma, PhD
Yuchou Chang
Yuchou Chang, PhD
Yanlai Chen
Yanlai Chen, PhD
Zheng Chen
Zheng Chen, PhD
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