We consider numerous criteria including academic performance, letters of recommendation and industry experience. We also consider GRE scores, TOEFL/IELTS scores (if relevant), motivation, work experience, awards, honors, prizes, and other accomplishments. Because master's applicants are so diverse, no single set of criteria adequately covers all the cases.
Please note: There are no eligibility criteria for application, such as minimum GPA or GRE scores (but see recommended minimums for English-language test scores below).
Factors we consider when evaluating applications include:
- Academic performance: The GPA is not the only criterion. The grades in data-science related areas are also important. Also, we take into account the fact that at some very competitive schools it is very difficult to achieve a high GPA.
- Letters of recommendation: Letters must give a detailed, factual, and candid evaluation of the applicant's capabilities. Rankings and comparisons with other students are very useful. Ask your recommender to follow these guidelines. Remind your recommenders of deadlines to ensure they are met.
- Personal Statement: The statement that accompanies your application is an important element that helps us learn more about you. There is no required length or topic, but we would like to learn more about your background and expected future in data science at a minimum.
- Work experience: We regularly accept applicants who have had work experience after their undergraduate degree, both in data science related fields and not. Not all applicants have work experience, but for those who do, a good description helps us better evaluate your application.
- GRE scores: These scores let us compare the basic skills of applicants from diverse backgrounds. We are aware that (1) test performance can improve considerably with practice, (2) some people do not perform well on tests, (3) and the verbal GRE is harder for some foreign applicants. The GRE is not required for the 2021 application cycle.
- TOEFL and IELTS scores: Applicants whose native language is not English and who have not received a college degree from an institution where the instruction is in English must take the TOEFL or IELTS exam. Additional evidence (e.g., certificate of completion of an English course) may also be submitted. We generally do not consider applicants who have scored below 620 (PBT) or 260 (CBT) or IBT (105), and prefer scores higher than that. The corresponding minimum IELTS score is 7.5. More information.
- Awards, honors, and prizes: Unless they are well-known (e.g., NSF fellowship or graduation with honors), please give details about them (how many candidates? how many awards? what were the selection criteria?). This is especially important for foreign applicants. If these awards are really important, we would expect your recommenders to mention them.
- Research experience: Research experience is not required for master's applicants and many of our applicants do not have any, but you can use experience you've had to demonstrate your ability to handle graduate-level data science material.
The Data Science Initiative (specifically, a group of faculty members) evaluates your application and makes recommendations to the Graduate School, which typically follows our recommendations. Therefore, you are generating your application (in particular, your statement) to be read primarily by the faculty of the Data Science Initiative. You will be notified by the Graduate School if you are admitted.