Moulik Shah is a skilled professional with diverse experience in machine learning, software engineering, and data science. Notable roles include Machine Learning Engineer at Bipolar Factory, where extensive work on computer vision models was conducted, and contributions as a Machine Learning Researcher at NYU Stern School of Business focused on developing an LLM-powered sentiment trading system. Experience also includes working as a Data Scientist at Miko, developing a recommendation engine and optimizing NLP pipelines, and serving as a Quantitative Research Analyst at Sykes & Ray Equities (I) Ltd., developing algorithmic trading strategies. Educational qualifications include a Bachelor of Technology in Electronics and Telecommunications Engineering from Dwarkadas J. Sanghvi College of Engineering and a Master of Science in Computer Engineering from New York University.
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