Statistics Machine Learning

I am an analyst at Statistics Canada, working with the Longitudinal and International Study of Adults (LISA) survey. I spent 2020 on a year rotation at Statistics Canada's Data Science Division, where I completed large data science projects for clients such as Health Canada and the Public Health Agency of Canada (PHAC). My research focus is not concrete as my projects have ranged in topics including natural language processing and reinforcement learning. I am enthusiastic and passionate about data science and am credited with starting the first Kaggle Competitive Group at Statistics Canada.

I completed my B.Econ with a minor in Statistics at Carleton University. My undergraduate thesis, The Impact of Substance Abuse in Tennessee: The Relationship between Low Birth Weight and Substance Use During Pregnancy, was advised by Michel Demers. It examines the percentage of low birth weights as a result of neonatal abstinence syndrome (NAS). The aim was to further understand how the opioid crisis has affected pregnancies. I am currently exploring Graduate studies for Computer Science.

At LISA, I often pitch how data science and automation can improve the survey processes and have successfully implemented data science tools into the LISA pipeline. These include anomaly detection, North American Industry Classification System (NAICS) code classification, and IBM-WATSON ICD-10 code classification.