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Job Category : Information Technology & Services
Duration : Long-Term
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
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, Propensity models, customer segmentation 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
Ability to work well under pressure in a fast-paced environment
Professional, service oriented, proactive and flexible
Post-graduate degree from a renowned institute in Engineering/Statistics/Economics/Computer Science/Mathematics (with a strong quantitative background)