Category: Admissions

Countdown to the Application Deadline

The January 18, 2019 deadline to submit your application to the M.S. in Data Science program is quickly approaching. As the deadline gets closer, the admissions staff will post advice on steps you can take to strengthen your application.

Application Advice Part 1: Letters of Recommendation

We pride ourselves on the intimate cohort experience we offer students. However, because we are a selective program, we must turn away hundreds of qualified applicants each year. Strong letters of recommendation are often the key to admission as they can provide valuable insight into an applicant’s intellectual abilities and personal qualities.

Choosing your recommenders. Two letters of recommendation are required; three are preferred. For applicants with professional experience, we recommend at least one academic reference and one professional reference. It is usually most helpful to submit academic letters of recommendation from instructors or research advisors in quantitative or technical disciplines who know you well and can speak to your ability to succeed at the graduate level. Do not seek out letter writers with prestigious titles only because you think their status will impress us. We want to see sincere letters from faculty or professionals with whom you have worked directly.

Guiding your recommenders. To help guide your references, you should educate them about the M.S. in Data Science program; let them know why you are applying to our program specifically; and show them your resume and essay responses. By taking these steps, you will position your references to write well-informed letters of recommendation that complement the other components of your application and strengthen your application overall.

Our main goal is to identify applicants who are extremely well prepared for academic and professional success in data science. To that end, we use a holistic review process to evaluate factors that we know have a bearing on success, including academic excellence, intellectual curiosity, technical and quantitative abilities, leadership, communication skills, creativity, and critical thinking. Our evaluation of these factors is based on: 1) your academic record, 2) your professional experience, 3) your motivations and preparation for graduate studies in data science, and 4) your personal qualities that will enable you to succeed as a data scientist.

1. The academic portion of our review is comprised of the following:

• Transcripts. We look at your field of study, overall GPA, major GPA, grades in prerequisites, grade trends over time, and other courses you completed.
• Academic letters of recommendation. The most informative letters come from instructors or research advisors in quantitative or technical disciplines who have evaluated you in more than one course and can provide specific examples that speak to your ability to succeed at the graduate level.

This portion of review is more important for students who just graduated from another program because they are less likely to have significant professional experience.

2. The professional portion of our review is comprised of the following:

• Resume. Your resume must concisely outline your education, work history, internships, publications, and extracurricular activities. Your resume should enable us to identify your unique strengths and experiences.
• Professional letters of reference. The most informative letters are from supervisors or colleagues who know you through direct involvement and can speak about the impact of your work, as well as about your key abilities and strengths.

3. Your motivations and preparation for graduate study are reflected through the following:

• Essay1: Why UW MSDS? The best responses describe short-time and long-term plans, how an M.S. in Data Science will help you achieve your goals, and why the UW MSDS program is a good fit for you.
• Transcripts. Strong grades in prerequisite courses are an indication that an applicant is prepared for graduate study in data science.

4. The final area of consideration is your personal qualities. We look for traits that are highly sought by industry employers, including communication skills, critical thinking, leadership, and creativity.

• Essay 2: Data Visualization. The best responses offer insight into your ability to critically and creatively think about and discuss data science visualization.
• Essay 3: Leadership. The best responses are authentic and original and provide detailed insight into your unique leadership style.
• Letters of recommendation. We look for insight into your personal qualities by evaluating what your letter writers say about your unique attributes and skills.

An application does not have to be perfect to be successful. We understand that you may have faced adverse circumstances in the past. This is why we offer you the opportunity to write an optional essay that may explain any gaps in your application or that may contextualize your academic background or professional history.

Due to the high volume of applications we receive, it is not possible to provide feedback on application materials, and reviewers cannot provide feedback on why an application was rejected. All admissions decisions are final.

As the January 18, 2019 application deadline gets closer, the admissions staff will post advice on our blog on steps you can take to improve your application.