GRE scores

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

For more information, visit http://gsas.nyu.edu/admissions/gsas-application-resource-center/2017-programs–requirements–and-deadlines/data-science.html.

Below, we provide more details about our expectations.

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 2017 intake cycle, the average GPA was 3.69. 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):

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 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

We require that students submit standardized tests scores for the GRE. There are no exceptions: we do not accept “out of date” scores; nor do we accept scores of other, similar tests; nor do we allow waivers (regardless of previous educational attainment or circumstance).

We require that students submit standardized tests scores for the GRE. There are no exceptions: we do not accept “out of date” scores; nor do we accept scores of other, similar tests; nor do we allow waivers (regardless of previous educational attainment or circumstance).

We wish to emphasize that we have no set minimums for the GREs, and we consider the totality of an application when making a decision about admission. Nonetheless, to the extent that it is helpful to give applicants a sense of the “ball-park”, what follows are the averages for the current cohort of MSDS students:

Average GRE Quantitative: 167.58

Average GRE Verbal: 157.36

Average GRE Writing: 3.65

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.

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. We prefer all letters on letterhead.