Bio

Manuel main interest is the optimization of business decision-making, by designing and implementing actionable applications and solutions that model the business data and ecosystem to maximize its value. Using techniques and algorithms derived from fields such as probabilistic modeling, statistics, information theory, collaborative filtering, digital signal and image processing (DSP and DIP), big data architecture, artificial intelligence (AI), natural language processing (NLP), data mining, deep learning and machine learning. Expertise building, mentoring, grooming, guiding, managing and leading Data Science teams composed of Data Scientists and Developers He has worked on a wide range of domains such as Oil and Gas, Finance, Education, Telecommunications, Energy Production, Computational Biology, Speech Recognition, Audio and Image Processing, Search Query Understanding and Information Retrieval. He holds several American patents and has over 30 publications on top research journals and conferences Proficient in the use of: C #, Scala, Java, Javascript, Spark, Python, Matlab, Cosmos, Hadoop, TensorFlow, Scope, Azure ML, R, SQL, , NoSQL, Hive, Ansible, Elastic Search