~12 years of experience in data science and business analytics includes in consulting environment. ~6 years of experience in mentorship and training for Data Science folks. ~1000+ students have been trained and mentored in data science space. ~ have extensively exposure on data science projects in the business function of Healthcare (Payer & Provider) Analytics & Marketing Analytics, Pharmacoepidemiology Research-Real-World Evidence Analysis. Extensive exposure on Patient-centered outcome research, outcome and quality measure development and evaluation, quality improvement program implementation • Value-based care model development and implementation • Innovative clinical and payment model evaluation • Statistical and economic modeling • Managing and analyzing a variety of large-scale data sets, including healthcare claims, patient-level assessment data, and national longitudinal survey data. A quantitative researcher with advanced training in health economics, statistics and analysis of real-word data. A skilled team leader and project manager with experience executing projects, leading multidisciplinary teams in a matrix organization, and collaborating to support strategic initiatives and business development activities. -Extended expertise in data science by successfully completing "Executive program in Data Science" from "IIM-Lucknow" -Published multiple white papers towards using statistical methods in marketing campaign and product associations in retail industry.  Industry Competencies: - Healthcare, Life Sciences, High-Tech, Retail, BFS.  Functional Competencies -- -Pharmacoepidemiology Research, Healthcare Outcomes / Real World Evidence Research leveraging real world data. -Healthcare Analytics (Claims Denial, Fraud waste and abuse, Claims Overpayment, Claims -Review. -People Analytics (Employee Attrition Models, Call Center Effectiveness ) -Credit Risk Modeling(PD), Campaign Response Modeling -Point of sales replenishment model -Marketing Mix Modeling/Marketing Analytics (Cross Sell, Up-sell models), Campaign ROI analysis.  Data Science Algorithms -- - Supervised/Unsupervised Machine Learning Solutions. - Natural Language Processing - Deep Learning: CNN, RNN, LSTM based solutions i.e. image processing, OCR, speech recognition etc. - Healthcare Utilizations (Cost/Visit) Models Poisson, Negative Binomial Model, Gamma Model, Two Part Model MR/LR, Principal Component Analysis  Technology Capability-- - Python - Pyspark - RStudio, Rshiny - Cloud Computing - Azure ML - SAS - Teradata SQL Assistant - Analytics Visualization etc.  Quality Credentials: - Certified Six Sigma DMAIC Green Belt from Genpact 2012