• Developed backend Python, Perl, and Bash scripts to accelerate development, improve infrastructure, and integrate with existing deployment tools for end-to-end statement processing.

• Scraped websites for financial assets data using Python libraries such as Requests, BeautifulSoup and Pandas to build comprehensive and clean datasets

• Conducted price prediction through linear regression, effectively predicting future prices of the validation dataset with 90.45% accuracy using the trained model with the lowest mean squared error

• Patched switches and diagnosed network connectivity issues

• Utilized various imaging tools, such as Clonezilla and Sysprep, for hardware deployment

• Created extensive documentation detailing relevant troubleshooting processes

• Ensured device connectivity to campus-wide network, as well as to virtual desktop infrastructure

• Troubleshooted hardware, software, and networking issues for point of sale (POS) systems