About

Paras Chaudhary is a highly motivated and task-oriented graduate student pursuing a Master of Science in Computer Science degree with a specialization in Machine Learning from Columbia University's School of Engineering and Applied Sciences. With a bias towards and excitement for the applications of Artificial Intelligence methodologies in the field of finance, Paras is a published researcher who appreciates the field-agnostic nature of data and its related learning models. He is proficient in Python, with a deep understanding of machine learning libraries such as Tensorflow, Scikit Learn, and Keras. Paras has taken up internships as a Machine Learning and Quantitative Researcher for Wealth Management Firms in New York City, delving into rigorous core Computer Science and Finance coursework. He complements his obsession for data with his ability to visualize it for the end-user, being proficient in multiple front-end frameworks like React, React Native, Vue.js, etc. Through his years of CS education, Paras has exposed himself to multiple tools of development that have helped him create sustainable production-ready applications, including Git, Spark, Jenkins, AndroidStudio, and AWS services like API Gateway, CloudFormation, CloudFront, CloudWatch, CodePipeline, Cognito, EC2, Lambda, Lex, RDS, Rekognition, SageMaker, and S3. Currently, Paras works as a Software Development Engineer at Amazon, where he specializes in Product Knowledge Graph. Before that, he worked as a Chief Research Assistant at Columbia University in the City of New York, where he initiated research to create and embed Machine Learning models of Technology Adoption in System Wide Agent-Based Network Simulations. He also worked as a Quantitative Researcher at Sauma Capital LLC, where he implemented 13 Machine Learning-based returns estimators, coded an exhaustive backtesting module, and automated the selection of the best portfolio option for a client based on financial measures of risk/returns like Sharpe and Calmar Ratios. Paras holds a Bachelor of Technology degree in Computer Science from JIIT and a CORe Credential of Readiness from Harvard Business School Online. He is also pursuing a Master's degree in Information Systems Management from Carnegie Mellon University. Paras is proficient in ML, Software Engineering, NLP, Research Science, AWS, Keras, Sagemaker, Spark, Scikit, Javascript, Tensorflow, Jenkins, Frontend, XGBoost, Python, VueJS, React Native, and Android. He has 0.27 years of relevant experience.