As a part of Advanced Data Science team, responsible for delivering end-to-end advanced AI / DS projects to clients, worked upon-- Clinical trial site optimization engine using MILP CBC solvers and site behavior forecasting using Dynamic Time Wrapping with Pulp, Python- Clinical Trial Site Performance Imputation Models to expand the trial site search space- Anomaly Detection Models for various domains of Clinical Trial Data using using algorithms like KNN, Isolation Forest, AutoEncoders

Data Science Lead in Big Data Solutions Team, responsible for delivering end-to-end Data Science, NLP, AI projects to enhance customer experience through predictive and prescriptive modelling

Customer Engagement Analytics - Developing solutions to enhance Customer Engagement & Satisfaction using latest advancements and innovations in the field of Data Science- text analytics- deep neural networks - LSTMs, custom ANNs- reinforcement learning- clustering, semi-supervised clustering- ensemble modelling: boosting, bagging, stacking

Using advanced analytics, data science to reduce cost and increase revenue while enhancing customer experience at Customer Service Department of Lava• Research – Identifying right service cost, measuring field cost inefficiencies, gaps in customer service & setting targets• Audit Analytics – Data driven identification of potential frauds at service centers, their magnitude & preventive steps• Business Planning for increasing revenue through Lava accessories and appropriate pricing of out-warranty services• Leading MIS team, with advanced analytics, creating new reports and dashboards as per business requirements

Role - • Developing and maintaining end-to-end automated Machine Learning models for sales prediction incorporating product specifications, prices and planned inputs of the organization using Python• Retailer wise Lava Model Sales Target Setting and Placement Norm Setting for approx. 1.5 lac across India• National Level Statistical Sales Forecasting using Product Availability, Retail Level Inputs and Historical Daily Retailer wise Lava Sales (approx. 90 lac row data)

• Was selected as the Bloomberg Champion• Responsible for mentoring students, teachers on use of Bloomberg for data gathering, analysis and research accross various domains

• Assiting National Development team in developmental work like organizion events with the TFI partners and impact reporting• Analyzing geographical landscapes to strategize for the potential partnerships with corporates