Predictive Modelling and Churn Reduction

● Reduced churn by 9% through pre-paid campaigns to targeted customers using supervised ML techniques using Apache Spark, Python, H2O, ML Ops, ML Flow, and Adobe Campaign Manager.
● Reduced churn by 10% through Pay Monthly campaigns by identifying customers who likely accept the offers using Supervised Machine Learning techniques in Microsoft Cloud Azure ML Eco System.
● Appraised vendor tools for the ML Observability & performed value analysis on the buy Vs build.
● Built the "ask" bot as a question-answering NLP-based application that helps new team members quickly get the source data availability and the name of the Database, Tables & Views.