Loveesh is a seasoned technical expert in machine learning, natural language processing, and advanced analytics. With over 9 years of experience, he has developed extensive computational and analytical expertise in a diverse domains such as eCommerce, Mailing, Shipping, Telecom, Sports and Retail Analytics. Over the years, Loveesh has mastered building solutions that are typically based on algorithms like XGBoost, GBM, Adaboost, Random Forests, SVM Linear and Logistic regression, either written in Python or R. Frequently used libraries include Numpy, Matplotlib, Seaborn, Pandas, Scipy, Scikit-Learn and NLTK. At Ugam, Loveesh is responsible for leading several projects that directly impact clients’ top and bottom line. Prior to Ugam, Loveesh has worked with leading companies like PayPal, Gulf-State Toyota, Fiat, and Microsoft and has helped them achieve best analytical practices, establish thought leadership and drive a highly motivated team.
Loveesh holds a Bachelor in Computer Science from Mumbai University and an MBA from a premiere institute. In addition, he has multiple specializations in deep learning, machine learning, and data science from deeplearning.ai, IBM and John Hopkins University respectively.