15 years of experience in inventing, improving and applying AIML and optimization techniques to support various business initiatives and programs with a view of achieving overall business targets and KPIs: (1). Experience in developing Data Science and Analytics Roadmap and Strategy (2). Experience in Integrating business understanding with analytical capabilities to deliver business value to stakeholders (3). Experience in enabling data-driven decision making and proactively identifying opportunities to drive business growth. (4). Expert in creating wide range of analytics solutions that converts structured/ unstructured data into actionable business insights, driving change for differentiated customer experience. (5). Experience in data extraction, data transformation and building models using wide Variety of programming tools like SAS, Python and Spark (6). Experience in hiring data science talent and providing leadership to data scientists in achieving their career goals and ensuring the data science capabilities are increased (7). Experience in driving AI/ML Operating model: Data commercialization & Monetization & Governance Business Problems: • Marketing: cross-sell/ up-sell, Next Best Action, campaign optimization, recommendations engines, OMNI channel customer experience • Risk, Fraud (trust, safety & identity): Credit risk modelling (A, B & C-Score), Fraud/Anomaly detection, Account takeover (ATO) detection & prevention, safety & identity analytics, and AML strategy • HealthCare & Insurance: Underwriting, auto-adjudication and payment integrity, Patient risk modelling, provider profiling and management, Pharmacy Benefit Management, Clinical NLP & NER for drug extraction from free text • Operations Analytics: collection strategy, HR analytics, call volume forecasting, CSAT analytics, intelligent call routing, call volume reduction • AI Governance: ML governance strategy, model monitoring and explainability Teaching Experience: • Been Lead instructor for data science at various organizations • More than 450 hours of teaching experience • Received strong endorsements Data Science Capabilities: • Supervised Learning: Generalized linear models, Decision trees, Random Forest, Bagging and Boosting learning, SVM, Neural Networks. Recommendation Engines using FM, Deep learning (Deep & wide, Deep & Cross, Deep FM) • Unsupervised Learning: NLP, Clustering, PCA & auto-encoders Time series models : RNN & LSTM, ARIMA , volatility modeling (GARCH), Co-integration models