About

Rahul Singh is a highly skilled Chief Analytics Officer and Co-Founder at Sigmoid Analytics with over 13 years of experience in the field of Artificial Intelligence, Machine Learning, Data Science, and Data Engineering. He is passionate about building intelligent machines that can sense, understand, reason, innovate, take decisions, make choices, have goals, learn themselves, take feedback, can be trained to achieve any goal and so on. In his current role at Sigmoid, Rahul is responsible for helping Fortune 500 organisations with their business transformation journey and defining a near-term strategy in Data, AI/ML, Technology and Cloud. He leads a team of experts in the cutting-edge technologies and research and provides services in Strategy Consulting (Data, AI, Analytics, Technology, Cloud), Data Science, Data Engineering and Managed Services. His belief in an expert-driven culture gives him an edge over his competition and helps him solve problems where others fail. Prior to Sigmoid, Rahul worked as a freelance IT Consultant, providing services in the field of Data Analytics, Machine Learning, Data Mining, Natural Language Processing, Recommendation System, Social Network Analysis, and Semantic applications. He has worked on projects for Automotive, Healthcare, Retail, E-Commerce, and Social Media industries. Rahul is a Senior Software Developer with experience in developing content-based recommendation engines for e-commerce product databases to Facebook user profiles. He has expertise in RDF, SPARQL, NER, Dbpedia, Apache Stanbol, Facebook Graph API, Couchdb, Gate, Jape, Stanford Parser, OpenNLP, JSON, XML, and other technologies. Rahul holds a B.Tech/M.Tech degree in Electrical/Instrumentation Engineering from the Indian Institute of Technology, Kharagpur. He is a highly skilled professional with a passion for solving extremely complex problems and creating innovative solutions. Rahul is looking to connect with like-minded professionals, researchers, and thought leaders in the field of AI, Maths, Machine Learning, Statistics, Knowledge Modeling, who are passionate about building intelligent machines.