I have a Bachelor of Science with a major in Mathematics from the University of British Columbia. My education was general, and covered topics including Probability, Statistics, Computer Science, and more esoteric Mathematics (Analysis, Abstract Algebra). I am extremely proficient with Excel (over a decade of experience), SQL and Python and since graduating, I’ve been familiarizing myself with even more technical skills such as Tableau and PowerBI. I consider myself a general quantitative problem solver: I enjoy diving into new areas and leveraging my skills to develop insights and solutions. I’ve also tutored Mathematics for years, across various levels. This has given me invaluable experience with communicating technical ideas in an engaging and understandable manner. I think this is especially useful in being a Data Analyst, where oftentimes the overarching goal is to produce technical insights for nontechnical parties.
Given historical sales and customer data, I performed exploratory data analysis and implemented an ARIMA model in Python. This allowed me to forecast future sales and identify factors affecting sales.
Given a subset of passenger data from the Titanic shipwreck, I used Logistic Regression Analysis to predict which of the remaining passengers survived. All work was completed in Python, in a Jupyter notebook
Using Java, I simulated a 2 species ecosystem (Lynx and Hares) on an individual level. The simulated data was then analyzed in Excel, which showed the expected coupled population curves.
Given a large, unordered retail store dataset, I created various statistical insights related to profitability of different items, departments, and regions.