Senior Manager - Data Scientist - Machine Learning + Advance Analytics

Senior Manager - Data Science - Gurgaon

Primary Responsibilities:

- Lead a business vertical and drive the thought leadership and strategy for pioneering and implementing advanced analytics solutions to solve business problems in healthcare

- Big Data analytics infrastructure comprising Hadoop, Revolution R, Visual SAS and SAS Fraud framework, R, Python, HIVE to solve complex business problems in Healthcare Domain

- Work with the business teams to operationalize the analytics solution for problems in areas of Fraud Waste and Abuse, Provider Operations, Provider Experience, Transaction Operations, Customer Engagement and Experience, Industrial Engineering and Advanced Forecasting techniques

- Be a trusted partner for the business stakeholders by understanding their business and strategy

- Manage client and program engagements using governance models

- Engage in client communications for all important functions including data understanding/exploration, strategizing solutions, etc.

- Manage a large team of analytics professionals to deliver analytics solutions and provide feedback to inform learning trajectory necessary to shape up the individuals for larger roles

Required Qualifications:

- Graduate/Post-graduate degree in: Statistics/Economics/Econometrics/Computer Science/ Engineering/ Mathematics/MBA (with a strong quantitative background)

- Extensive experience in the Analytics/Data Science industry

- Significant programming experience with SAS, R, Python, Machine Learning, H2O, HIVE, and SQL, etc.

- Exposure to Data Visualization and Business Intelligence tools/packages like Tableau, R Shiny and D3.js is ADVANTAGE

- Strong practical knowledge of econometric/statistical methods like Linear Regression, Logistic regression, Generalized Linear Model, Survival Analysis, Sampling Techniques, Design of Experiments, Time series analysis, CART, CHAID, Multivariate Techniques like Clustering, Discriminant Analysis, Principal Component Analysis, Factor Analysis, or Multidimensional Scaling, etc.

- Strong theoretical and practical knowledge of Machine Learning techniques like Random Forest, Neural Networks, Support Vector Machines, Gradient Boosting, Bagging Techniques, or Genetic Algorithms, etc.

- Strong practical knowledge of primary NLP applications like OCR, Pattern Recognition, Auto Coding, Advanced Text Analytics, and Information Extraction

- Excellent analytical and problem solving, including the ability to disaggregate issues, identify, root causes and recommend solutions

- Excellent presentation skills; ability to organize and present information to suit the needs and understanding of the audience

- Ability to work well under pressure in a fast-paced environment while demonstrating good level of maturity

- Professional, service oriented, proactive and flexible