Client is a leading, global ten provider of custom information technology, consulting and business process outsourcing services, and serves primarily Global 2000 companies. The firm employs more than 150,000 people and works with 805 active clients across banking & financial services, insurance, healthcare, life sciences, retail/consumer, manufacturing, energy, communications, and media. Since being spun-out as a public entity in 1998, the company has grown at an unprecedented rate, with anticipated revenue of >$8, making the fastest growing IT services company over the last 10 years, and certainly the most profitable now featuring a market capitalization greater than $18B. Client is a member of the NASDAQ-100 Index and the S&P 500 Index and part of Fortune 500 list.
A graduate with a Bachelor s Degree in Computer Science or Engineering Discipline, Data Science or equivalent training and experience. Concentrations in AI/ML preferred. 2) Must have 3-7yrs Experience on AI/ML (Artificial Intelligence & Machine Learning). 3) Preferable Expertise in leveraging capabilities of AI & ML with medium to large customer data in Insurance Domain. 4) Expertise in full product life cycle from idea generations on real customer use cases , building/leading the proof of concepts, and finally to implement for very large scale customer base. 5) Deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. 6) Solid grounding in statistics, probability theory, data modeling, machine learning algorithms and software development techniques and languages used to implement analytics solutions. 7) 3+ years of deep experience with AI/ML platforms, technologies, Frameworks (e.g. Sci-kit Learn, TensorFlow, Apache MXnet, Theano, Keras, CNTK, Spark, Caffe, Open NLP, Pandas etc.) 8) Experience with one or more of the following: Natural Language Processing, sentiment analysis, classification, pattern recognition. 8) Strong expertise with Classification & Regression models like Random Forest, Logistic Regression, KNN algorithm etc. 9) Proficient with one or more general purpose programming languages like Python, java and other important ML and analytics languages (e.g. R, Scala). 10) Experience using and adapting to new technologies. 11) Scaling out ecosystems in the ML/AI space. 12) Familiar with the ecosystem of software vendors in the AI/ML space. 13) Ability to think strategically about Customer experience, business, product, and technical challenges. 14) Good Analytical skills and ready to take up challenge as independent resource. 15) Good Knowledge on Mathematics and Statistics will be nice to have.
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