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

• Fall 2023 Priority Deadline: April 6, 2023
• Fall 2023 Regular Deadline: May 18, 2023