When people hear the word physics, many think about the world of quantum mechanics and time travel and Avenger's Endgame plots, and rightfully so.  Personally, I prefer to think about a physics degree as a 4 - 5 year course in problem solving.  In order to excel in that kind of field, you need to be adaptable and quick-thinking, and able to apply lessons and theory taught in one context, to a field which might seem initially completely unrelated.  Contrary to the techniques of memorization which are often taught in high school, at a higher level it is required to think more deeply about problems in order to succeed.

It's for that reason that after finishing my degree in physics, I elected to pursue a career in data science.  It had always been an interest of mine, and with such a rigorous training in math, science and problem solving, as well as some decent coding experience, I was well placed to apply my skills coming right out of undergrad.  I took the Data Science Bootcamp from BrainStation, and have been developing my skills further at NIKU Farms ever since!

I am particularly interested in solving business problems through the lens of data science, either through basic data wrangling techniques or more complex ML models.  As you'll see below, my expertise includes all the cutting edge data science packages (scikit-learn, TensorFlow, etc.), as well as visualization tools like Power BI and Plotly.  I'm a lifelong learner, and I try to take on projects which keep with that philosophy - my current project of interest is an ML model looking to predict the outcome of regular season NBA games.  In my spare time, I like to keep active in rec sports leagues (volleyball and soccer are my favourites), and hitting up the gym as much as possible!  Also a big time fan of all things music, and my dog, Spike, AKA Spikers.

If you have any questions, or if you know of any opportunities which sound like a fit for me, or if you want to chat about collaborating on something, please don't hesitate to reach out!