AMAR JEET KUSHWAHA

● Developed and implemented RFM (Recency, Frequency, Monetary) and product propensity models, leading to improved conversion rates and effective customer segmentation for targeted marketing campaigns. ● Successfully implemented a Fraud Rule Engine, resulting in a savings of Rs. 32L in cashback within a span of 2 months by identifying and preventing fraudulent users on the platform. ○ Credit risk assessment and prevention. ○ Identifying creditworthy users on the platform using alternative(device) data. ○ Early identification of default users. ● Developed propensity models for various products, including Virtual Credit Card (VCC), Buy Now Pay Later (BNPL) with an 11% increase in approval rates, and Rentals with a 2% increase in conversion rates. ● Scoring mechanism for customers to prevent fraud in (VCC and BNPL). ● Led initiatives in cashback optimization for customer retention, utilizing advanced models and rule engines to optimize customer retention costs from Rs. 34 to Rs. 21 , resulting in increased profitability and improved customer loyalty. ● QuickSight Dashboard (Build Several Dashboards). ● Proficient in geospatial data mapping, including reverse geocoding (converting lat-long coordinates to pincode), enabling accurate location-based analyses. ○ Geo mapping boosts our rental model by 30% MOM in the beginning of the project, helps to identify the right customer. ● Skilled in performing similar user clustering and targeted marketing for rental products, leveraging geospatial data and customer segmentation techniques. ● Collection Model:- ○ Improvement in collection by 6% 30 DPD(40% to 34%). ○ Reduce the load of the calling team(30%). ○ Prenotification to the FOS agent helps to plan the route in a better way. ● Build a Geo Reverse Encoding system an alternative to google map API. ○ Can map 3cr lat-long to pincode in 11 min. ● Collaborate cross-functionally with teams such as marketing, finance, and engineering, ensuring seamless integration of analytics insights into product development and marketing strategies. ● Utilized diverse data sources such as appographic data, SMS data, and visit data to augment traditional transactional data, enabling the creation of a comprehensive 360-degree view of the user base

● Developed Data monitoring tools (Audi, Mercedes-Benz, VW). ● Data scraping tools saved the 9hr of the testing team. ● Shop location mapping by google map scrapping , google search scraping, natural language processing. ● Develop the customer segmentation tool for Audi.

● Automated data processing pipeline. ● Acquiring data from primary or secondary data sources and analyzing data by using statistical techniques and providing ongoing reports. ● Sanity check tool(sync data between oracle and Athena). ● Bugzilla Monitoring tool(prepare the report to see the performance of employees).