Behind the Scenes: CDS Admissions Podcast Season 2

NYU Center for Data Science
3 min readMay 28, 2020

For prospective students, making a decision on where to spend years of your life in a graduate or post-graduate program is incredibly difficult. CDS’s Admissions Podcast tries to make that decision easier by presenting conversations between our current students and host Tim Baker (CDS Program Administrator for Academic Affairs and Admissions.) On the first season, Tim explored topics such as finding housing, transitioning to life as NYU as well as many 1-on-1 conversations with current CDS students about their experience. We interviewed Tim about the upcoming season of the podcast and what he learned from Season 1:

The following has been lightly edited for clarity.

To refresh everyone’s memory, how did the first season of the podcast come to be?

During the admissions process, we received a lot of inquiries from prospective applicants that were interested in learning about the program from the student point of view. Obviously, this was not something that I would be able to provide, but I wanted to create a platform for our students to share their experience in the program with potential applicants. I thought who better to sell our program than our students. I had a wish list of students that I wanted to speak with, students who I knew would be great ambassadors for the MS and PhD programs. I also wanted to be sure that I spoke with part-time, full-time, 1st year, 2nd year, international and domestic students, people involved in the Leadership Circle and students who were strictly pursuing the academics, PhD students who started in our MS program and transitioned to the PhD program, and PhD students who came from industry. Ultimately I wanted to present a well-rounded population of students who could champion our program to future generations.

What’s the biggest lesson you learned from producing season 1?

I need to be quiet while people are answering questions. I say “OK” entirely too much while attempting to fill the pauses. I wish I started earlier in the year, so that once the admissions process started the podcasts were ready to roll. By the time I started recording the podcast we were already into the admissions season. So the mixing schedule suffered a bit because time was tight. I think next year I want to cast a wider net. Some of my favorite episodes were from students who I had not previously interacted with.

Are there any changes you’re making to the podcast for season 2?

For Season 2 I am thinking about taking a different approach from the one on one interviews, though I will probably keep them as well. For Season 2 I want to have more group discussions. Let groups of 3 or 4 students go more in-depth on topics. Whenever we have an event for new or prospective students we have student panels and I think the energy of our students bouncing ideas and experiences off of one another plays really well to an audience. I also want to move beyond the realm of admissions. As the program expands there are so many more avenues for sharing. We launched an undergraduate program, the Women in Data Science group, the COVID-19 research initiative. There is so much interesting and important work happening at the center, I think it would be exciting to share these stories through the podcast.

Is there a guest or topic for season 2 that you’re looking forward to covering?

I am excited to talk with our returning students in the fall to see how COVID-19 has impacted them and how they found ways to cope and thrive. Also, Andrea Jones-Rooy and I have started work on a few episodes exploring the going-ons at the Center for Data Science. I am interested in seeing where this idea can go. You have a data scientist and a lay-person exploring this emerging field. I think it can bring forth some interesting episodes.

The CDS Admissions Podcast is available on Apple Podcasts, Spotify, or wherever you get your podcasts online.

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NYU Center for Data Science

Official account of the Center for Data Science at NYU, home of the Undergraduate, Master’s, and Ph.D. programs in Data Science.