Data Science FAQ

When and how can I apply? Does the program have rolling admissions?

The Data Science master's program uses the online application for the Harvard Graduate School of Arts and Sciences. You will find it here.

We do not have rolling admissions. There is a single application deadline each year - December 1st.

How can I find the Data Science master's program in the GSAS application system?

You will find the Data Science master's degree in the GSAS online application under the listings for Engineering and Applied Sciences. On the Degree Program Selection page choose "Engineering and Applied Sciences" as the program, "Data Science" as the Area of Study, and "S.M." as the degree.

Am I eligible to apply to this program if my undergraduate degree is in economics, business, or some other non-STEM field?

As an interdisciplinary field, Data Science attracts students with varied backgrounds. We welcome applicants with undergraduate training in a wide range of academic disciplines.

What prerequisites are necessary for applicants to the Data Science master's program?

Prerequisites we expect from applicants include knowledge of calculus and linear algebra; familiarity with probability and statistical inference; fluency in at least one programming language such as python or R, and an understanding of basic computer science concepts.

If my undergraduate degree is not in a STEM field, how can I show that I have a sufficient technical background?

If your training in Computer Science, Math and/or Statistics is not reflected in the courses listed on your transcripts, you will need to find other parts of the application to make your training clear to the Admissions Committee. The Additional Materials section of the application is available to upload relevant information. You can also describe your training at one of your jobs or through self study in your Statement of Purpose.

Do all of my recommendation letters have to be from academic sources?

You should get letters of recommendation from the three people you think will be able to make the best case for why you are an outstanding applicant for this degree program. These should be people who know you and your capabilities very well. Former professors can certainly be valuable sources of recommendation letters, but letters from managers or colleagues from your work experience can also be helpful.

Is a writing sample required for the application?

No, a writing sample is not required.

Is the GRE required?

The Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) will not be accepting General GRE scores nor Subject Test GRE scores for applicants to our Ph.D. programs or masters degree programs in Computational Science & Engineering and Data Science.  Applicants to these programs should not submit official or unofficial GRE scores to us nor mention them anywhere in their application materials.  

Questions about the SEAS GRE policy and requirements should be directed to the SEAS Office of Graduate Admissions at

There are minimum scores required for the TOEFL or IELTS. International students required to take those tests must achieve at least a sore of 80 on the TOEFL or 6.5 on the IELTS.

Can I pursue the Data Science master's degree part time while I am working?

The Data Science master's degree is a full-time on-campus program. All students are required to be registered full-time (i.e. take four 4-credit courses each semester). All of the courses students will take while in the program are offered during the day and require students to be present on campus.

Can I apply to both the Data Science and CSE master's programs?

No, applicants should not apply to both the Data Science and CSE programs. Applicants should select the program that best fits their preparation and interests and apply to that particular program.

Is there financial aid available?

Currently, Harvard is not providing financial aid for APCOMP master's programs; however please be sure to check the APCOMP page on financing your master's degree and also this GSAS page for general information about funding for graduate programs.