At DaVita Kidney Care, I support a ~$450M revenue budgeting process and own a $33M annual OpEx budget across 15 departments. My driver-based forecasts and monthly P&L analysis help identify revenue changes, spending variances, and data errors.
I developed a SQL-based inventory risk forecasting model that helped Purchasing reduce monthly inventory waste by 40%, from $20K to $12K. I also built logistics cost models with Python and Excel to evaluate carrier migration scenarios.
I developed a Glean AI agent for monthly P&L variance screening, reducing daily investigation time by 83% and shortening the month-end close cycle by 40%. I also automated ERP-to-Anaplan data extraction and reconciliation, replacing an 11-tab Excel workflow with a 14-second process.
At Cherry Bekaert, I automated validation and reconciliation across more than 1 million transactions and 500 tax files using Python. At Behaivior, I developed machine learning workflows for wearable-device data that improved classification accuracy from 32% to 65%.
