Job Description:

• Be an Individual Contributor in the Analytics Research and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies.
• Be a part of large delivery teams working on advanced projects when expert assistance is required.
• Deliver advanced Data Science capabilities to businesses in a meaningful manner through successful proof-of-concept solutions, and later on smoothly transition the proof-of-concept into production.
• Leverage, big data analytics infrastructure comprising R, Python to tackle previously unsolved problems across Fraud Waste and Abuse, Provider Operations, Provider Experience, Transaction Operations, Customer Engagement and Experience, Clinical Services etc.
• Conduct evaluations and assessments of new tools and technologies to ensure that the team stays at the frontier of Analytics.
• Write White Papers to evangelize ideas and drive adoption with the broader enterprise 
• Present in leading conferences to showcase expertise and solutions

Required Qualifications:

• Individual Contributor with 8 to 10 years of experience in Analytics/Data Science
• Post-graduate degree from a renowned institute in Engineering/Statistics/Economics/Computer Science/Mathematics (with a strong quantitative background)
• Demonstrated hands-on experience in solving real-world problems using Natural Language Processing and/or Image Processing
• Demonstrated hands-on experience in using algorithm libraries / frameworks like H2O, Keras and TensorFlow
• Expert level programming ability in R and/or Python and possess good presentation skills with the ability to organize and present information to audiences with disparate levels of technical understanding
• Strong theoretical and practical knowledge of some or most econometric/statistical methods like Linear Regression, Logistic regression, Generalized Linear Model, Survival Analysis, Sampling Techniques, Time Series Analysis, CART, CHAID, Clustering, Discriminant Analysis, Principal Component Analysis, Factor Analysis, Multidimensional Scaling etc.
• Strong theoretical and practical knowledge of some or most Machine learning techniques like Random Forest, Support Vector Machine, Gradient Boosting Machine, XGBoost etc.
• Strong theoretical and practical knowledge of some or most Deep Learning techniques across Recurrent Neural Networks, Convolutional Neural Networks etc.
• Consistent track record of building and successfully deploying advanced analytics solutions with demonstrable value to the organization
• Excellent consulting skills, including the ability to engage with and present to CXO leaders as well as stakeholders with minimum to high analytics exposure across various departments in an organization
• Excellent analytical and problem solving skills, including the ability to disaggregate issues, identify root causes and recommend solutions
• Ability to work well under pressure in a fast-paced environment
• Professional, service oriented, proactive and flexible