As a contractor I worked under a Fortune 500 company to handle raw data from third-party vendors. Many projects utilized Python with the Google Cloud Platform to schedule regular transfers of data from Cloud Storage buckets into a BigQuery table via Google App Engine and Kubernetes Engine jobs. I then subsequently cleaned this data to the specifications of the client.

I worked closely with the faculty research team to collect and analyze quantitative and qualitative data in order to better understand the needs and focuses of ethical technology in the tech industry. This involved using Python and Beautiful Soup for scraping data from several popular job boards to better understand the content of these job listings. I assessed the popularity of key terms and skills through a combination of popular NLP techniques and Emsi's Skill Extractor API. I also used R and PowerBI to visualize influential terms and other points of interests (such as the titles and locations of these jobs) from the dataset.

I used R, ggplot2, and SQL in redeveloping part of the bank’s Current Expected Credit Losses (CECL) model, and presented my findings to the bank’s model validation team. The linear regression model I proposed was subsequently put into production. In addition, I assisted our bank’s treasurer by examining the relationship between online service usage and account behavior. This project included several visualizations, predicting account behavior using random forest classifiers, and forecasting attrition rates with survival analysis techniques.

My primary role at this company was overseeing customer’s orders, investigating any instances where a customer was overcharged or undercharged for the services they requested. If I discovered such a discrepancy, I would fix the payment information, which helped our accounting department tremendously. I also edited several promotional decks that were used in our CEO’s sales pitches to prospective clients.

I reached out to multiple local businesses for promotion in our Annual Meeting Guide, helping ensure the project was ready in time for publication. This process involved calling local businesses, organizing their information for my co-workers, and handling cases where a business was not able to be reached via telephone.