• Led model monitoring and maintenance for consumer and small business credit card acquisition models.• Developed tools in Python to detect and address model and data drift.

• Helped factory managers anticipate the number of semiconductor wafers that will be delayed in shipping to the customers by building a machine learning model using Quantile Random Forest in R that predicts weekly On Time Delivery percentage.• Developed a dashboard using Python(Pandas) and Qlikview that displays financial and operational KPIs of manufacturing sites, helping the executives generate the quarterly business reports.•Helped factory GMs clean up a total of $1.5 Billion worth… Show more • Helped factory managers anticipate the number of semiconductor wafers that will be delayed in shipping to the customers by building a machine learning model using Quantile Random Forest in R that predicts weekly On Time Delivery percentage.• Developed a dashboard using Python(Pandas) and Qlikview that displays financial and operational KPIs of manufacturing sites, helping the executives generate the quarterly business reports.•Helped factory GMs clean up a total of $1.5 Billion worth of inventory by data wrangling the inventory data using Python (Pandas) and developing a dashboard in Qlikview that displays the dollar amount of inventory with their categorization, location in the factory•Drove KPI-based initiatives to get new products to market faster by developing a Qlikview dashboard that displays the daily status of new products in the factories, thereby, introducing transparency in current business process Show less

• Replaced Excel-based inventory monitoring approach with a Qlikview dashboard to help a manufacturing site monitor daily inventory and save ≈10 hours/week of manual work.• Defined a dashboard migration process to deploy the dashboards from QA to production environment resulting in an increase in the number of Global Manufacturing dashboards in production from 2 to 18