About

Prabhat Jha is a highly skilled Quant Analyst at JPMorgan Chase & Co. with a passion for data science and engineering. With over 1.87 years of relevant experience, he has gained expertise in various areas such as Data Scientist, Keras, Computer Vision, Python, NLP, ML, Tensorflow, Pandas, Neural Networks, Naive Bayes, XGBoost, Random Forest, Seaborn, RNN, Word2Vec, Deep Learning, Scikit, and Research Scientist. Prabhat holds a Master's degree in Statistics - MStat from the Indian Statistical Institute in Kolkata, where he also served as a Placement Coordinator. He also has a Master's degree in Statistics - MStat from the Indian Statistical Institute in New Delhi, and a Bachelor's degree in Mathematics and Computer Science from the Chennai Mathematical Institute. Currently, Prabhat works as a Modeling Analytics Analyst at JP Morgan, where he is responsible for analyzing and modeling complex data sets to provide insights and recommendations to the business. He is also a Data Science Engineer at Finneza, where he leverages his skills in data science and engineering to develop innovative solutions for the company's clients. Prabhat is a highly motivated individual with a strong work ethic and a passion for learning. He is always seeking new challenges and opportunities to expand his knowledge and skills in the field of data science. With his extensive experience and expertise, he is a valuable asset to any team and is dedicated to delivering high-quality results.