Data Science Manager having 12 years of experience executing data-driven solutions to increase efficiency, accuracy, and utility of data processing across domains healthcare/life sciences/Retail/CPG. Work cross functionally with stakeholders to ensure data-driven answers are provided and recommended. Implemented, and managed health economics and outcomes research projects, including but not limited to quality of life studies, retrospective database analyses, economic models, chart reviews, qualitative research, and systematic literature reviews. Experienced at creating data regression models, using predictive data modeling, and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems. Hands on development experience with R/Python or related statistical software package including programming skills in building and deploying machine learning models (supervised & unsupervised, time series) . Familiarity with decision techniques including optimization, regression, decision trees, neural networks, cluster analysis, Time series prediction , mixed models using big data technologies is required. Working experience on auto ML tools like H2O driverless and Data Robot for predictive modelling & forecasting. Worked on resolving multiple healthcare business problems like identification of patients at risk of chronic disease, Implementation of auto medical encoding for diagnosis & CPT using NLP, Image classification of Skin cancer using Deep learning CNN model, identification of factors explaining patients at readmission risk, OCR implementation to examine physician note, etc. Hands on experience with XGboost, light GBM, CNN, RNN, LSTM, k-NN, Naive Bayes, SVM, Random Forest, Lasso & Ridge & Logistic Regression.