Here are samples of my work as a Data Scientist and Software Engineer.

Web Scraping

Web Scraping with Beautiful Soup — A Use Case

In this project, we obtain data from a webpage, i.e., we do some web scraping, using Python and libraries such as Requests to get the data and Beautiful Soup to parse it. As an example, we will show how to obtain a list of a couple hundred names and addresses from a particular website, and use it with other packages to format the data into an easily imported CSV file.

Find more in Towards Data Science and GitHub.

When Data is Scarce

When Data is Scarce… Ways to Extract Valuable Insights

We provide insights into the Freedom of Information Requests of the Region of Waterloo. This dataset is relatively small and Machine Learning can’t be used effectively. We, therefore, use a variety of Natural Language Processing (NLP) techniques, descriptive statistics and exploratory data analysis, to learn more about this data and extract valuable insights.

Find more in Towards Data Science and GitHub.

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Impact Amplifier of the KWCF

At Zeitspace, we take on the mission of having pro-bono projects. One of them was the Impact Amplifier web app of the Kitchener-Waterloo Community Foundation.

Find more in this Zeitspace blog post.

NCIM

Web App for Cycling Events

At Zeitspace, another project was a web app that ranks riders competing and training at the Mattamy National Cycling Centre. Having riders sorted out in races according to their skill level is necessary to have safe races. Beginners and experienced riders in the same race just don’t mix.

In this project I acted as a Data Engineer, as I built a data pipeline that involved cleaning, parsing, and extracting useful information from excel files that had multiple formats.

I also helped to take an automated approach to ranking cyclists. Find more about this contribution in this Zeitspace blog post.