Matthew Reyers

B.Sc. Operations Research, M.Sc. Statistics
Data Scientist
Zelus Analytics

The distinguishing factor in my education was the hands-on experience. I did an undergraduate in Operations Research, which is a blend of Computer Science, Mathematics, and Statistics. Although the program is quite comprehensive with capstones and course projects, the real fun came through hackathons. I competed (poorly) at a few local hackathons. Regardless of the outcome, I found the connection between my skills and the projects I cared about. I even used my work from a hackathon as the basis for my Operations Research capstone project. Through hackathons and similar competitions, I found my passion for sports analytics. 

I went on to do my Master's in Statistics when I got to the end of my undergraduate and felt incomplete. I didn't have the pieces to complete the puzzle. The Master's, for me, put it all together. The course work, the cohort, and the faculty consistently improved my understanding of the world around me. I also learned the value of engagement. There is a tangible benefit to competing in hackathons and other miscellaneous projects, one I might argue is a bigger benefit than the education itself! The courses I completed came across as afterthoughts to employers during interviews. On the other hand, the hackathons and other projects I completed had employers calling me. The best example was the NFL Big Data Bowl; my team (consisting of Lucas Wu, Dani Chu, James Thomson, and myself) was invited to present in Indianapolis to a field of NFL Executives. Talk about a hiring fair! Win or lose, NFL executives were contacting all the presenters in the weeks after the presentations to try to attract the top talent to their team. I didn't get nearly the same engagement when I added another semester of course work to my LinkedIn page. 

I am currently working for Zelus Analytics. Based out of Austin, Texas, Zelus Analytics is a baseball analytics start-up focusing on building champions. The company is built around statisticians and leverages their excellence to build better models than what is currently available, providing client teams with a competitive edge.  As a statistician/data scientist, I am tasked with all the elements of development, ranging from model building to model deployment. I find myself constantly challenged and engaged by both my work and my coworkers, closely mimicking my experience during my Masters at SFU. The most interesting aspect of my work so far has been the exposure to the full life cycle of projects, as my education covered only the first step (model building). Fortunately, hackathons and side projects covered the rest.

Follow Matthew on Twitter at @Stats_By_Matt