Master of Science in Data Science Program Requirements
Master of Science (M.S.) in Data Science Program
Department of Mathematics and Computer Science
McQuaid Hall; (973) 761-9466; [email protected]
Data Science Program
Faculty: Anand; Kahl; Minimair (Program Director); Saccoman (Chair); Wachsmuth
Senior Faculty Associate: Sethi
Adjunct Faculty: Abayomi
Associated Full-Time Faculty: Goedert; Hale
Data science comprises the concepts, techniques, tools and body of knowledge supporting Big Data, the acquisition, management, analysis and display of large, rapidly changing, and varied sets of information. It supports the extraction of actionable knowledge directly from data through a process of discovery, or hypothesis formulation and hypothesis testing. Data science encompasses activities ranging from collecting the raw data, processing and extracting knowledge from the data, to decision making based on the data, implementing a solution. The data science field presents career entry, advancement and transition opportunities for practitioners and researchers in industry, government and academia at various levels of expertise.
A data scientist is a practitioner who has extensive knowledge in the overlapping realms of business needs, domain knowledge, analytical skills, and software and systems engineering to manage the end-to-end data processes in the data life cycle. Such a practitioner is skilled in data management and processing, analyzing business and scientific processes, and communicating findings for effective decision making.
The Master of Science in Data Science Program equips students with the knowledge and competencies required to become data science and analytics professionals. Applying tools and methods such as probability theory, statistical analysis and computing, and exploring subjects such as data collection, manipulation, processing, analysis and visualization, the students learn how to solve data-driven problems and practice analytics-driven decision making. Furthermore, students learn how to automate these activities by cloud computing and machine learning platforms as the amount of accumulated data grows immensely.
Graduate applications are considered on a rolling basis with no application deadline.
General Admission Requirements
Applicants must submit the following materials (please note that an application will not be reviewed until all required materials have been submitted):
- Completed Graduate Application with Fee
- Personal Statement
- Three Letters of Recommendation
- Applicants must have completed undergraduate mathematics through the level of Calculus 2 and Linear Algebra and Statistics. Please see note below.
Are you missing any of the math or computing prerequisites for the program? We will help design a one-semester/summer transitional curriculum to help you acquire the necessary skills before starting the M.S. program. Please contact Dr. Manfred Minimair at [email protected] for details.
Admission Requirements for International Applicants
In addition to the general admission requirements for the M.S. in Data Science program, international applicants must submit the following additional materials:
- Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS) scores. This requirement can be waived if English is the official language of an applicant’s home country.
- Transcript evaluation: Transcripts from institutions not accredited in the United States or Canada must be evaluated, course-by-course, by the World Education Service (WES) or another evaluation agency that is accredited by NACES.