About

Neel Doshi is a versatile professional with experience in various fields, including machine learning and data science, finance, and web development. He is currently working as a summer technology analyst at Credit Suisse, where he is applying his skills in data modeling, artificial intelligence, big data, and data mining. Neel has participated in several national hackathons and worked on various machine learning projects. He has also published a paper on handwritten recognition using PyTesseract and implemented a project for the same. In addition to his expertise in data science, Neel is also a quant enthusiast. He has previously interned at two algorithm trading companies, where he created custom strategies for clients tailored to their needs. He has also implemented them on AmiBroker and Tradetron. Neel's finance knowledge includes certification from National Stock Exchange - India, as an Equity Derivatives Trader. His final year undergrad project was on an adaptive and automated currency trader, which involved studying historical forex currency data using Neural Networks and predicting future trends. This prediction helped facilitate profitable trades, and he has published a paper for the same in SAE. Neel is also an experienced web developer, having created websites at his internship at DotSyndicate and for a chain of grocery stores in New Jersey called Park Deli. His web development skills include HTML, CSS, JS, MySQL, MongoDB, and ReactJS. Neel has a Master's degree in Computer Science from Rutgers University-New Brunswick, where he is currently pursuing his studies. He has also worked as a teaching assistant at Rutgers, where he taught a course on Data 101, which includes R programming to undergraduate students. He has also been responsible for grading assignments and exams of 230+ students for CS 205 (Introduction to Discrete Structures). Overall, Neel is a highly skilled professional with expertise in machine learning, finance, and web development. He is a quick learner and has a passion for solving complex problems using technology.