Applying to MSA program

The Master of Science in Analytics (MSA) at NC State is one of the country’s most elite graduate data science programs. If you’re skeptical, check out the MSA’s job placement ratings and the accompanying salaries. Being one of the premier data science institutions, the competition to get into the program is fierce. A record number of students applied to the MSA in 2018, and only 14% were accepted. But acceptance into the MSA is not based on random chance. There are ways to strengthen one’s application, and there are mistakes that can jeopardize the chances of even the most qualified applicants. As a current student at the MSA, I can provide advice for applying to the MSA based upon my firsthand experience.

If there is only one piece of information you take away from this blog post, let it be this: there is no typical student at the MSA. Successful applicants come from a variety of backgrounds. Don’t believe me? Check out this year’s current student roster. Individuals of a variety of ages are represented at the Institute with some having just completed their undergraduate degree and others coming from careers spanning decades. Don’t be intimidated by the accomplishments of successful applicants from previous years. Remember, if you were already a renowned data scientist, you would not need to apply to the MSA. A significant aspect of the admissions committee’s decision is based on your openness to learning and continuous self-improvement.

That being said, you must at least possess a solid foundation in statistics. Head of admissions Valerie Schwartz says, “The number one reason applicants get rejected is because they lack the necessary prerequisites in statistics.” Having prior coding experience is helpful, with SAS, R, and Python being the most common languages employed at the Institute. 

While the MSA does not favor applicants of a certain academic major or age, the admissions committee is looking for candidates that meet certain criteria. All of my classmates are smart. Many graduated with academic honors or even as valedictorians. However, do not make the mistake of equating high GPAs and test scores with golden tickets to Willy Wonka’s Chocolate Factory. In fact, the MSA does not even consider GRE or GMAT scores as part of the admissions process. Being intelligent is necessary for getting accepted to the MSA, but it is definitely NOT sufficient. The Institute is looking for candidates with a hunger for knowledge— the students who choose to enroll in difficult classes out of genuine curiosity. The MSA is searching for students that combine high-achieving drive with the willingness to put the good of the team ahead of individual ambitions. Such characteristics cannot be gleaned from GPAs or test scores.  

For this reason, the personal statement and your three letters of recommendation are critical pieces of your application. The personal statement, in particular, is your opportunity to show (not tell) why you would be a great fit at the Institute. One of the biggest mistakes people make in their personal statements is spending too much time gushing about the wonders of data analysis. Says Valerie Schwartz, “We don’t need to see in a personal statement why data science is important—we know that already; that’s why the MSA exists!” Instead, Valerie recommends applicants write about topics such as, “what sparked their interest in analytics, in what direction they hope to take their career, and why they believe NC State’s MSA program is a good match for their professional goals.” Avoid simply reciting what you listed on your resume. Instead, provide context for how the items on your resume fit with your passion for analytics. For example, I talked about my interest in politics and electoral forecasting in my personal statement. The subject pertained to analytics, it was a different topic that made me stand out as a candidate, and it was something I could enthusiastically talk about during my admissions interview. Of course, if you’re uninterested in politics or healthcare or finance or sports, then don’t write about these topics! But as long as a subject excites you and is relevant to data science, you can put together a great personal statement.

As for letters of recommendation, make sure to pick individuals who you know from a professional or academic context. For younger applicants, mentors for research projects and supervisors from internships are fantastic references! Seek out potential recommenders early on, and give your recommenders advanced notice about the application deadline.

Be sure that you fully understand the MSA program before you submit your application. Valerie Schwartz says, “The most successful applicants have done their research: they have a solid rationale for pursuing the MSA program and have taken steps to strengthen their candidacy.” If you have questions about the admissions process to which you can’t find answers on the Institute’s website, reach out to the admissions team. They are always willing to address prospective student inquiries and provide direction for those who are just beginning to consider whether the MSA is a good fit for their professional goals. I sincerely hope you consider applying to the MSA, and I wish you the best of luck!

Columnist: JT Klimek