Master’s in Data Science

Admission Requirements

Overview

Admission to NYU’s Master of Science in Data Science is extremely competitive. This speaks both to the popularity of the field of Data Science and to the very high calibre of students who we seek as part of our program.

Without exception, you must submit the following to support your application for admission:

• TOEFL or IELTS; however, TOEFL is preferred (Required for all applicants whose native language is not English and who have not received a university degree in an English-speaking country)
• Official college transcripts
• Three letters of recommendation (we prefer all letters on letterhead)
• Statement of Academic Purpose
• (optional) Personal History Statement
• (optional) GRE scores

For more information, visit the graduate schools application resource center.

Educational Prerequisites

Successful applicants to the MSDS come from many different undergraduate backgrounds, including degrees in Statistics, Computer Science, Mathematics, Engineering, Economics, Business, Biology, Physics and Psychology. In the 2023 intake cycle, the average GPA was 3.80. Our students’ transcripts usually include As and Bs (only), and we expect stronger grades in more relevant subject matter (see below) from those coming from less selective institutions. Regardless of degree, we require specific and substantial knowledge of certain mathematical competencies, and some training in programming and basic computer science.

To be considered for the program, you will be required to have completed the following (or equivalents, e.g. MOOCs certification or course credit):

• Calculus I: limits, derivatives, series, integrals, etc.
• Linear Algebra
• Intro to Computer Science (or an equivalent “CS-101” programming course): We have no set requirements as regards specific languages, but we generally expect serious academic and/or professional experience with Python and/or R at a minimum.
• One of Calculus II, Probability, Statistics, or an advanced physics, engineering, or econometrics course with heavy mathematical content

Preference is given to applicants with prior exposure to machine learning, computational statistics, data mining, large-scale scientific computing, operations research (either in an academic or professional context), as well as to applicants with significantly more mathematical and/or computer science training than the minimum requirements listed above.

Work Experience

Many of our students join us directly from undergraduate, but we also very much welcome evidence of relevant work experience—and clear employment goals once the MSDS is completed—in data science.  Past experience and career aspiration goals can be related to commercial industry, government, academia or some other sector.

Standardized Tests

GRE General Test is optional. If submitting, please note: we do not accept “out of date” scores (see FAQs here); nor do we accept scores of other, similar tests.  

If submitting scores for the GRE General test with your application, please upload a PDF of the unofficial scores, which are made available upon completion of your test, to the “Additional Information Section” of your application. This is in addition to sending your official scores to the Graduate School of Arts and Science.

We also require evidence of proficiency with English as a second language for certain students who must provide it. For those students, we generally require a TOEFL score of at least 100 overall (and have strong preferences for better scores), and per university guidelines, will not admit those falling below that threshold.

For additional information regarding standardized testing please visit the Graduate School of Arts and Science’s FAQ Page.

Three Letters of Recommendation

Recommendations for admitted students are invariably excellent, with references holding applicants in the highest esteem relative to other students or employees with whom they have interacted in the past several years. References from professors or employers who can comment directly and in a detailed way on the applicant’s case, aptitude for, and attitude to data science projects are treated with the most weight. Though not required, we prefer all letters on letterhead.

For additional information regarding letters of recommendation please visit the Graduate School of Arts and Science’s FAQ Page.

International Students

Answers to common questions that international student applicants may have can be found in the Graduate School of Arts & Science’s Application Resource Center. 

In particular, questions regarding what degree must an applicant have in order to enroll are addressed here. If you have further questions about your degree eligibility, please contact the GSAS Graduate Enrollment Services team at gsas.admissions@nyu.edu. 

Information about international transcript evaluations and other information about being an international student at NYU can be found here.

Internal Transfers/Current NYU Students

We do not allow internal transfers from other NYU graduate programs. If you are a current NYU graduate student and you would like to be a part of the NYU Data Science MS program, please note that you are required to submit a new application.

Ready to Apply?

If your background meets the majority of these requirements, and you have a desire to develop the methods to harness the potential of data, then we encourage you to begin the application process. Please proceed to the Graduate School of Arts and Science webpage to apply for admission. 

Prior to starting your application please review the Graduate School of Arts and Science’s general application policies page.

For more questions, email us at cds-admissions@nyu.edu.

Deferral Requests

The Center for Data Science will not approve a request for deferral of admission. If an admitted student wishes to delay enrollment, it will be necessary to turn down the offer of admission and reapply for admission the following year. A completely new application will be required. The new application will be considered along with all other applications at that later time.