TA Spotlight: Leo Lamontagne
Leo Montagne is a TA for CS 7646: Machine Learning for Trading. Keep reading to learn more about Leo!
What do you do professionally?
I currently work as a quantitative developer for a private equity firm. We do some financial modeling and implement web apps to help the investment teams. Prior to this, I worked at a couple startups as a machine learning engineer. Originally, I went to graduate school for materials engineering, doing computational research and simulations for energy materials such as batteries and photovoltaics. I enjoyed the computational aspect much more than the lab work, so I pivoted into machine learning.
Why do you TA for OMSCS?
Because I enjoy it! It is very rewarding to help students grasp some of the more complicated concepts. I love it when the conversation goes beyond questions directly related to an assignment and we start talking about real world applications and big picture topics in machine learning. I find myself also learning a lot and doing some more research based on the discussions we have.
What is your advice for future OMSCS students?
I would advise students to take it easy and go at their own pace. I initially wanted to finish quickly and pretty soon felt like I was burning myself out. I found the program much more enjoyable when I cut back to one course a semester, and I think I got more out of each individual course this way. If work and life are going to be busy, there is nothing wrong with taking a semester off.
What's your best study hack?
I try to find little ways to reward myself for getting various tasks done. For example, after I review a couple chapters of material, I’ll let myself watch the newest episode of some TV show, or after I finish a practice exam, I’ll treat myself to some ice cream. I also try to divide up my studying into small chunks and spread it over several days. I absolutely cannot just devote an entire weekend afternoon to studying all of the material at once.