- Implemented periodic Dynamic Segmentation of B2B customers which will group their customers as HIGH or LOW on the basis of their monetary value and divide their customers as ONTIME or DELINQUENT on the basis of their payment behavior using various clustering algorithms. - Led a team of 15 interns working on Payment Date Prediction and Dynamic Segmentation use cases of Collections for clients across the globe. - Predicted the payments/Invoices clearing dates using Regression Algorithms. This Model helps the B2B Clients to track and remind their customers regarding the closure of their invoices before they make any delay of the payments. It leads to help in reducing DSO of our clients.- Worked on R&D for building Promise to Pay use case. Was associated on testing its feasibility and data gathering.- Designed an algorithm that will stack-rank the customers, and will help to plan a collector's day by identifying the high-risk bad paying customers which will lead to a smooth collections process.

-Developed and deployed AI-Enabled Solutions for 5+ Live Clients that will predict the payment date of an invoice when it gets created in the system. This model has been adopted by companies to proactively identify delayed invoices, reduce manual efforts, increase collector efficiency, and improve AR Strategies and Processes. - Understood the Order to Cash cycle followed in B2B world.- Created an automated live accuracy monitoring python script which monitors the perform of the live production accounts.- Created an automated script which can clean the data and gives us a preprocessed data which can be directly using for modelling.