- Developed a Decision Tree Model segmentation customers based on their credit bureau data to improve the Cost to Revenue Ratio for insurance campaigns, increasing the final conversion rate from 1.8% to 2.7% (1.5x).- Refreshed the existing income prediction model based on the customer's bureau data, the model has an accuracy of 66%, 20% gain over the previous model.- Gained a deep level understanding of customer's credit data (Equifax, Cibil, Experian, Highmark) and created customer level aggregation and segmentations to assist marketing team to create efficient strategies.- Developed new automated process in R/SQL, completely automating the consolidation and reporting of departmental reports. Thus, reducing the manual effort of 4-5 hours/day to an automated 30 mins batch process.- Created dashboards on Tableau to track agent/business performance and productivity on a day-to-day basis.