● Bootstrapped 3 NLP Text Classification Models in Python for predictive analytics on Invesco Application Database 

● Trained supervised models on validated labeled dataset to generate predictions for missing data with 74% accuracy 

● Cut down on 25% of inaccurate data within Invesco ServiceNow CMDB via Machine Learning Regression models 

● Alleviated cumbersome ETF quarterly performance write up processes by utilizing text summarization models 

● Created POC to showcase how leveraging NLG Transformers could cut down on 50% of write up process timeframe