● Leveraging Data Science and Machine Learning to improve people's health and make healthcare more affordable and accessible across the network of the #1 Healthcare Company in the world and #4 on the Fortune 500

● Improved order conversion rate of client products by 35% through email conversation analysis of 500K+ CRM emails using NLP● Organized and facilitated workshops to educate member firms about the latest Data Science tools and techniques

● AI Chatbot using Dialogflow's NLP (Python, Dialogflow, SQL, AWS, and Skype): - Automated 60% of ad-hoc tasks through chatbot; Integrated bot with SQL Server for database & deployed it over Skype; Through this bot, the client could get sales reports and KPI results in real-time● Topic Extraction and Sentiment Analysis (Python and R): - Performed topic modeling over 150K customer reviews for a European retail client using Latent Dirichlet Allocation(LDA) & Non-negative Matrix Factorization(NMF); Used NLP to capture customer reviews’ sentiments● Cross-sell Modeling (PySpark, R and SQL): - Generated €1.7MM quarterly incremental revenue for a leading Oil & Gas client through frequent item-set algorithms (Apriori and FP-Growth) using PySpark to identify cross-sell opportunities and better product placement● Geospatial Predictive Modeling and Analysis (R and QGIS): - Built statistical models to identify untapped locations of profitable retail stores for the client; Analyzed GIS data over a spatial platform and extracted Google Maps API data for store demographics● Self-Serving Interactive Dashboards (Tableau, Power BI and SQL): - Reduced people-hours spent by 75% by developing Self-Serving Dashboards using Tableau and Power BI for monitoring key metrics

● Propensity to Buy Modeling (Python, SQL):- Used AdaBoost Boosting Classifier to forecast probability for customers to purchase any SKU within various categories for Fortune 5 retail client; Tuned parameters using grid search which improved model accuracy to 89.3%● Customer Segmentation using K-Means (Python, SQL): - Determined statistical clusters based on demographic and shopping attributes for 81MM+ customers to enable better targeting and improving marketing effectiveness● Designed personalized campaigns; improved offer optimizations using A/B and multivariate testing resulting in $17MM sales lift

● Undertook 3 months intensive Data Science training and worked on multiple case studies of time series forecasting, segmentation and predictive modeling belonging to retail, telecom and aviation industries

● Worked on DMRC website using Joomla Framework and PHP, and managed its modules and content