Bloomberg Team #4

The project focuses on developing a pipeline to automate the onboarding and normalization of publicly available listed derivative exchange data for Bloomberg using a combination of machine learning models and cloud-based infrastructure. Data originates from multiple exchanges, with both structured public feeds and unstructured public documents such as PDFs, circulars, and memos.

The goal is to design a scalable ingestion and processing pipeline capable of dynamically classifying, extracting, and standardizing disparate data formats for further downstream analytics and validation.