Rebecca Nugent’s official title at Carnegie Mellon University (CMU) is associate department head of statistics. However, by the end of our conversation we wanted to call her “coach.” We caught up with her at one of Citadel’s 18 datathons and observed her coach students in understanding what she describes as the “arc of data science.” Later, when we walked across a quad at CMU together, she waved at some students and informed us that she’s the coach of the school’s Ultimate Frisbee team. During our conversation, Professor Nugent explained what it takes to see patterns in datasets and offered career advice for the next generation of data scientists.
Thanks for letting us join you today Professor Nugent. Tell us about when you decided to make a living in data science.
I always enjoyed math, but it wasn’t until a few months prior to starting my master’s program in statistics that I realized I was going to make a commitment to data science. I was thumbing through the Stanford course catalog in a car with my mother and I blurted out “I want to take all of these courses.” My mother looked over at me and we both knew I found my calling.
As I took more and more classes in statistics, I came to love a few things about this discipline. I observed how data science can have an immediate impact in helping address any number of societal problems. In addition, I was exposed to the many fields that statistics touches. As a curious person, I appreciated that statistics would enable to me to learn about so many other fields. Finally, I could see the different career paths that would be available to me down the road. In all, statistics kept a lot of doors open for me. I went through many of them.
You’re now in a statistics department that has been around for 50 years. Congratulations to you and CMU on the anniversary. What would you say are the hallmarks of the best and brightest students in statistics and data science?
CMU has overseen the development of so many bright mathematical minds over the past five decades. What separates great from good in this field is the ability to see the full arc of data science. Great students refrain from immediately jumping in and trying to solve the problem they’re presented with. Instead, they take a step back, ask questions, and identify the real problem they’re trying to solve. After they’re comfortable they understand the problem, they go through the following steps:
This last step is important. As data scientists, we must not only solve problems. We have to effectively communicate the results of our work. Communication skills are as important in this field as coding and modeling.
At Citadel, we believe it’s important to win with integrity. We try to do things the right way without compromise. What does it mean to act with integrity in data science?
We act with integrity when we question our results. There’s a temptation to extrapolate results. There’s also a temptation to discard evidence that disproves our hypothesis. We need to guard against these temptations in this field. I often tell my students to act ethically because your analyses will have a big impact on the world. I’m so proud of how committed our CMU students are to working with integrity. I’m confident they will influence others throughout their careers to act with integrity as well.
Speaking of careers, what advice do you give to your students as they get ready to leave school?
As my students prepare to start long and successful careers, I advise them to be confident in their skill sets. The demand for data science skills puts a weight on the shoulders of those with a background in statistics and related fields. However, I encourage students to see this demand as such a great opportunity. For 50 years, CMU statistics students have taken their skills into the real-world and shown that they can take on complex problems. I plan on being around to see students thrive for the next 50!