Senior Data Scientist
• Designed an exhaustive recommendation platform that classified the customers into different segments based on their current state of journey. The journeys were developed to personalize the marketing campaign. ROI per customer grew by 25%• Predicted the potential churning customers using XGBoost and targeted them with their preferred offers type. (Recall 90%, AUC = 0.87) Generating additional revenue of RM 1.3M• Identified the major pain point areas of VIP customers by understanding the sentiments of thereviews using Latent Dirichlet Allocation (LDA) which resulted in an increase of customer retention by 18%• Forecasted the daily footfall for the world’s largest hotel and optimized the price of the rooms for each segment using ARIMA, LSTM and Prophet• Based on demographic and behavioral parameters clustered the 6.5 million casino customers, to create the best marketing offers and promotion for each persona.• Build a recommendation system using Lasso regression to understand the customer preference towards different promotional mail and then target the customer based on the email features which were important. CTR of email response increased by 25%• Clustering Tool - Created a tool for cluster generation (Algorithm embedded - k-means, k-modes, GMM). Feature of the tool: Data preprocessing & exploration, Data Visualisation, PCA. Reduced the effort of an Analyst by a significant amount to perform the above task.