What is your name?
What was your graduation year?
What were your major(s)/minor(s)?
Computational Finance & Statistics
Where are you currently working or in school? What is your job title (if any)?
Director of Hockey Research, Pittsburgh Penguins
Where are you from originally? Where do you live now?
Pittsburgh PA; Pittsburgh PA
What drew you to the Carnegie Mellon Statistics program?
In Statistics classes, every assignment or project had a purpose and taught you an important concept. For me, Statistics provided an opportunity to work on interesting problems while also investing in my own intellectual capital and gaining skills that translate easily to the real world.
What was your favorite Statistics class or project? Which class do you wish you had taken?
My favorite class was Statistical Graphics & Visualization. The statistical intuition gained from working with so many datasets really stuck with me, and the focus on communicating (often complex) results from data to both technical and non-technical audiences in an easy-to-understand way has been invaluable to my career. I wish that I had done a senior thesis in Statistics, since working on a year-long research project under the supervision of one of the excellent faculty members in Statistics would have been great preparation for both graduate school and a future career.
Describe any research experiences or internships you had while at CMU. What did you like best about them?
After my sophomore year, I worked with Professor Bill Eddy on a project that involved statistical neuroscience and visualizing magneto-encephalographic data. The brain is pretty awesome, so it was fun to be exposed to this area of research as a sophomore. As a senior, I worked with Professor Rebecca Nugent on a project that involved web-scraping and analyzing data on US patents. Learning web-scraping as a student proved to be extremely useful, as it led to the publication of several papers and R packages that helped propel me to my professional career.
What did you do immediately after graduation? How did you end up in your current job/school?
If I remember correctly, I went to PHI. After that, I started in the Statistics PhD program at CMU. While in graduate school, I worked with Professor Andrew Thomas on research involving statistics in sports. We wrote a paper called "Competing Process Hazard Function Models for Player Ratings in Ice Hockey", published later in the Annals of Applied Statistics, which gave us some notoriety in the sports analytics community. From there, we built a website (war-on-ice.com) that quickly became one of the most prominent sources of data and statistical analysis of the NHL. We organized the Pittsburgh Hockey Analytics Workshop in 2014 and presented our research at various related conferences, building contacts in the industry. I was hired by the Penguins as a consultant in the summer of 2015, and Andrew began working full-time with the Minnesota Wild shortly thereafter.
Tell us about any CMU student clubs or organizations in which you were involved.
Club sports: Ice Hockey, Roller Hockey
Clubs: Actuarial Club, Carnegie Mellon Capital Management, Undergraduate Investment Club
What advice would you give to an incoming student or new Statistics major?
As an undergraduate, students face a tremendous amount of social pressure at CMU to get amazing, well-paying jobs in tech or finance. I joined a bunch of clubs and did a bunch of job interviews related to tech and finance because of this, but I was never really interested in those jobs, and I never really enjoyed any of the finance-related club activities. My advice: Carve your own path and focus on the things that interest you. I was pursuing jobs in finance/tech for all of the wrong reasons. Once I started focusing on what I was actually interested in -- developing new statistical methodology, working with sports data, and doing quantitative research in areas of science and social science that I found interesting -- I had much more success.
Which movie or TV character best matches your Statistics/Data Science personality?
If you could be any statistical distribution, which one would you be and why?
Definitely not Exponential or Geometric, because I don't want to be memoryless.