I'm a former student at the University of Calgary. I graduated in 2016 with a BSc in physics. I'm currently looking for work in applications of information theory to financial markets though I'd likely be just as happy doing any kind of data science.

I've worked with random numbers, MC/MCMC methods, simulated annealing, genetic algorithms, ant-hill optimization, Fourier methods, linear regression, Hough transform, correlation methods, Kolmogorov-Smirnov, Anderson-Darling, likelihood maximization, numerical solutions to PDEs, relaxation methods, and other associated topics in machine learning/data analysis to various depths.

I'm also familiar with concepts in network theory (small world property, power law link distributions in random and real-world networks, Laplacian spectra of graphs, etc.).

I'm comfortable with Windows and Apple OS but I hate both of them partially on principal (lack of open source, hostility towards user freedoms, and Apple's consumeristic culture of "cool") and partially due to my prevailing comfort with Linux. I run Kubuntu 16.X on my personal machine though I'm still running 14.X's version of KDE and am most at home with this distro.

I am competent writing in Fortran 90/95 and Python3 but I'm currently writing exclusively in Python3 so my Fortran has been getting rusty. I've also written in C++ but that was a number of years ago. I'm comfortable with LaTeX, GNUPlot, BASH (some scripting in BASH), Python's matplotlib, scipy, scikitlearn, and GTK+3. I've more recently been dabbling with HTML+CSS+JavaScript.