Lead Applied Data Scientist
Current• Played a pivotal role in building the Personlised.AI product, supporting backend operations for marketing campaigns, deploying AI modules, and training recommendation models for major QSR clients, leading to significant revenue increases.o Item Recommender: Developed a model to recommend top personalized products to customers.o Optimized Offer Recommendation: Created a system to suggest profitable offer amounts for marketing campaigns.o Customer Segmentation: Implemented models to segment customers for targeted marketing campaigns based on their life cycle stages.o Propensity Models: Built models to predict customer behavior, including churn, order, and offer redemption likelihood.o Market Basket Analysis: Conducted association rule mining to identify and recommend items frequently purchased together for cross-sale campaigns.o Look-Alike Modeling: Designed models to identify target audiences for campaigns by finding customers similar to a defined seed group.• Owned Product Deployments at Clients.o Actively contributed to planning various marketing campaigns focused on cross-sell, upsell, and retention, starting from digital app adoption, customer retention and churn mitigation, customer stickiness, and new item adoption.o Worked with the customer success team to measure campaign impact using various AB testing analytical groups.• Trained junior data scientists and machine learning engineers to scale up and sharpen their skillset.
