Master of Science in Data Science

Format: Online
Application Deadlines
  • Spring 2023 Priority Deadline: November 3, 2022
  • Spring 2023 Regular Deadline: December 8, 2022

The MS in Data Science (previously MS in Data Analytics) online degree program helps students earn the credentials and acquire the skills needed to enter or advance in the fast-growing field of data science. Ranked last year as one of the Best Value Online Big Data Programs, the MS in Data Science online degree program offers foundational knowledge and hands-on programming competencies, resulting in project-based work samples similar to that of a programming boot camp.

The program’s learning objectives and demanding, hands-on courses are designed around employer needs. Throughout their time in the program, students build portfolios of increasingly complex projects using popular programming languages such as R and Python, which mirror the current experience and demands of the IT workplace. Students build predictive and prescriptive models, practice giving presentations, and review each other’s work in a convenient online setting, ensuring that they are equipped with the expertise most valued in today’s marketplace. The MS in Data Science program culminates with a capstone project that represents highly sophisticated, but practical, solutions to address real world problems.

Additionally, the program’s faculty comprise committed and engaged technology practitioners who are experts in their fields.  They invest time in building courses on the use of open source best-practice tools that satisfy high employer demands for quality programming and use of advanced techniques.

Career Prospects

The MS in Data Science program prepares graduates for a variety of technical and managerial positions, such as data scientist, business intelligence analyst, knowledge engineer, informatics engineer, data analyst, data mining engineer, and data warehousing manager. 

Admissions Criteria

Applicants must possess a bachelor’s degree from an accredited institution, with a GPA of 3.0 or higher on a 4.0 scale. Applicants are required to write a personal statement, upload a resume, and provide two letters of recommendation. Letters of recommendation may be submitted before or after submitting an application. Please note that an individual interview may be necessary.

As an interdisciplinary field, we welcome applicants from diverse professional backgrounds. However, because the MS in Data Science is a highly quantitative and technical major as compared with MBA-like programs, acceptance requires applicants to demonstrate current skills in:

  1. Statistics and probability including descriptive statistics, skewness/kurtosis, histograms, statistical error, correlation, single variable linear regression analysis, significance testing, probability distributions, and basic probability modeling;
  2. Linear algebra including basic matrix manipulation, dot and cross products, inverse matrices, eigenvalues, representing problems as matrices, and solving small systems of linear equations;
  3. Programming in a high-level language such as Python, Java, JavaScript, C++, C, Ruby, or SAS (2+ years). Applicants must be able to write working code from scratch;
  4. Relational databases including connecting to and manipulating data, working with tables, joins, basic relational algebra, and SQL queries. Two or more years of experience with Microsoft Access can be substituted if the applicant is able to perform the same operations without using Access’s graphical interface; and,
  5. Analytical thinking including the ability to translate real-world phenomena into quantitative representations and, conversely, the ability to interpret quantitative representations with practical explanations.

Skills in these areas will be assessed in two ways:

  1. Completion of credit-bearing coursework with a grade of B or better from an accredited college or university OR 2+ years of relevant experience on a resume; and,
  2. Completion of a mandatory challenge exam that will assess current skill and knowledge in these areas. If you lack the skills required for admission to the program and/or are unable to answer the questions found in the challenge exam, please email datascience@sps.cuny.edu for recommendations on how to pick up the necessary skill sets.

Bridge Program

If you have completed credit-bearing courses in the above areas or have used these skills at work but are no longer proficient, we offer three bridge courses: R Programming, SQL, and Data Science Math. These bridge courses are intended to refresh knowledge and skills, but are not for individuals who are learning these topics for the first time. 

For questions, please email datascience@sps.cuny.edu.

Application Deadlines

  • Spring 2023 Priority Deadline: November 3, 2022
  • Spring 2023 Regular Deadline: December 8, 2022
Apply Now

Student/Alumni Profiles

Duubar E. Villalobos Jimenez

MS in Data Science 2019

"Since my master’s program was 100% online, I had the experience as to how to cope with online work activity. When COVID hit, and everything became remote, I was able to switch gears seamlessly.”

James Hamski

MS in Data Analytics 2017

"It’s not just about perception, I can “walk the walk” and produce results because of the skills I gained.”

Jonathan Hernandez

MS in Data Science

"The most enjoying aspect of the program is the fact that we get to work on real-world programs and can apply our skills learned in these courses to solve real-world data science problems."

Youqing Xiang

MS in Data Science

"There are four key success factors for a data analyst: computer programming and mathematical skills, domain knowledge, communication, and teamwork. CUNY SPS has prepared me in all of these areas."

Recent News About Master of Science in Data Science

Social Activism and Firm Valuation: An Examination of ‘Taking a Knee’ Protests and National Football League Sponsors

November 29, 2022

Review of Pacific Basin Financial Markets and Policies

Arthur O'Connor, academic director of the MS in Data Science and BS in Information Systems programs, co-authored the research study, "Social Activism and Firm Valuation: An Examination of ‘Taking a Knee’ Protests and National Football League Sponsors." The study was published in the Review of Pacific Basin Financial Markets and Policies.

Best Online Master's in Data Science Programs of 2023

November 15, 2022

Intelligent.com

Intelligent.com has ranked the CUNY SPS MS in Data Science program Best in the Northeast on its list of Best Online Master's in Data Science Programs of 2023.
Fortune Education Badge for Most Affordable Online Master’s in Data Science Programs in 2022

MS in Data Science Ranked #1 in Affordability by Fortune Education

November 15, 2022

In a second top ranking by Fortune Education, the magazine rated the program #1 on its 2022 list of most affordable online master's in data science programs.

Most Affordable Online Master’s in Data Science Programs in 2022

November 09, 2022

Fortune Education

The CUNY SPS MS in Data Science program has been ranked #1 on Fortune Education's 2022 list of Most Affordable Online Master’s in Data Science Programs.