Job profile description

Primary Responsibilities

 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

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