Money Team

Money Team

• Developed specialized modules for key algorithmic components to bolster intelligent supply chain planning and scheduling for company clients

• Developed a robust Python program to automate testing for complex data sets in order to verify and analyze the effectiveness of specialized supply chain modules. Designed a flexible, efficient data preprocessing pipeline for handling complex files with over 8 million lines, optimizing attribute extraction, data joining and restructuring.

• Enhanced the supply chain scheduling system to allow for configurations of various rules as a JSON input to the program for resource planning.

• Due to inaccuracies, the original algorithm was overscheduling the number of employees needed for weekly shifts in the airport, incurring unnecessary costs for the company. Independently diagnosed the problem and changed the code.

• The result increased accuracy by 83% and improved runtime performance by 41%. This was recognized by the CEO, as the improvement will save company costs by allowing resources to be used more efficiently and avoid resource underutilization.

• Using machine learning models to make live predictions for game results and data

• Independently developed and tested a full pipeline for automatically generating game highlights and uploading them as NFTs via Piñata and IPFS

• Built and tested using Python, Subprocess, Matplotlib, Ipfs, Truffle, Numpy, and other packages.