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data scientist
loyalytics•  August 2022 - Present
- Wrote highly optimized code to automate the analysis process. - Conducted non-starter customer analysis to understand their behavior, developed a K-means clustering model to group non-starters based on behavior and other properties, gaining insights into their characteristics. • Analyzed farmers by region and other properties, creating a K-means clustering model to identify suitable vehicle models and crops, and employed the K-prototype algorithm for an alternative perspective on farmer segmentation, successfully enabling TVSC to focus on desired customers. • Designed and experimented with new segments with low risk and high intent, conducted statistical analysis of financial data, and monitored portfolio risk, identifying segments with high risk. • Automated exploratory data analysis and customer profiling by developing a python library, reducing analysis time by 60%. • Implemented RFM customer segmentation with K-means clustering, and analyzed the segment be- haviour, enhancing customer targeting strategies. • Conducted fraud analytics, detecting cashier misuse of loyalty points and ensuring correct issuance to cus- tomers, resulting in increased customer satisfaction. • Designed key measurement metrics and schema structure for organizing campaign data, improving cam- paign tracking and effectiveness. Conducted A/B testing for campaigns, leading to findings that informed business decision-making and optimized campaign strategy, hence significantly increasing revenue. • Analyzed and executed targeted campaigns using the Loyalytics CRM tool SWAN AI, significantly boosting revenue and achieving a high ROI. Facilitated over 1 million enrollments in Lulu Group’s loyalty program through strategic campaigns, analyses and insights. • Created a comprehensive framework for promo impact analysis, optimizing promotional strategies and their impact on sales and customer behavior. • Devised key metrics for a Quality Control dashboard, improving data quality and operational efficiency of data pipelines, saving substantial time and enhancing data governance. • Developed a Customer Data Platform using the Medallion lakehouse architecture. - Developed churn model for the client and did churn analysis.
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JSS Academy of Technical Education
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