About

Rakesh Jayaprakash is a highly skilled Senior Software Engineer at QuEST Global with a versatile skill set. He is a quick learner, innovative, and hardworking individual with a passion for solving complex problems in machine learning and system engineering. Rakesh is a team player who can understand complex logic with relative ease and has an objective to be part of a progressive organization where he can utilize his knowledge efficiently to develop the organization. Rakesh has designed, implemented, and evaluated new models and rapid software prototypes and APIs to solve problems in machine learning and system engineering. He is capable of deep analysis of data required for data science and has worked closely with domain experts in cleaning text data, analyzing text data, text-pre-processing, handling imbalance data, training, and evaluating the model. He has built various ML models to resolve customer problems and automated the selection of machine learning models based on model accuracy. One of Rakesh's major contributions was developing a tool that reduces manual effort and time by automating the work sequence using the Machine Learning Model, which predicts Heads-up Decision for a technical variance provided by the customer through a click of a button using Excel Macro. He has also built an API for the Machine Learning Model developed and developed an automated scheduler with MSSQL to sync with the live day-to-day data and retrain their machine learning model. Rakesh has helped Exxon-Mobil to reduce manual effort and time and improve sales business using automation, text classification, and deep learning techniques. Rakesh has a Bachelor of Engineering degree in Computer Science from Global Academy of Technology. He has 4.61 years of relevant experience and is proficient in ML, software engineering, NLP, search, text classification, AI, deep learning, data science, and MSSQL. Rakesh is a highly motivated individual who is always eager to learn and improve his skills.