During my tenure, I actively contributed to various aspects of a product called Praexia. I wrote comprehensive unit tests to ensure its reliability and functionality. Additionally, I utilized pandas to enhance data display capabilities, providing a user-friendly experience.Furthermore, I took charge of deploying the Praexia product on Microsoft Azure, ensuring its smooth integration into the cloud environment.To gather relevant data, I developed a Python-based web scraper, enabling efficient data extraction. I explored Natural Language Processing techniques to model the scraped data, enhancing its understanding and analysis.In order to classify tenders as belonging to Praelexis or not, I implemented a logistic regression model on a dedicated tender dataset. Subsequently, I uploaded the list of predicted tenders onto a shared Google Drive using the PyDrive library.While working with a 1.5-year-old Django codebase, my focus primarily revolved around building tests for existing code that lacked proper testing, thus improving the codebase's overall robustness.

Tutoring/mentoring for Economics 114 and Economics 144

Tutor for Computer Science 114

I gained hands-on experience working with essential Python modules such as Matplotlib for data visualization and MySQL for database management. In this capacity, I was entrusted with the responsibility of uncovering meaningful patterns within the provided data and performing data queries to extract valuable insights specifically related to the company's product, smart watches.