Abhay Garg
About Abhay Garg
Abhay Garg is a Data Scientist II currently working at Bizongo in Bengaluru, Karnataka, India. He has previous experience as a researcher at Tata Research Development and Design Centre and has worked on various data science projects involving NLP, computer vision, and data mining.
Work at Bizongo
Abhay Garg currently serves as a Data Scientist II at Bizongo, having joined the company in 2024. His role involves leveraging data science techniques to develop analytical solutions. Bizongo is known for its focus on packaging solutions and supply chain optimization, where data-driven insights play a crucial role in enhancing operational efficiency.
Previous Experience at Tata Research Development and Design Centre
Prior to his current position, Abhay worked at Tata Research Development and Design Centre (TRDDC) as a Researcher from 2019 to 2022. During his three-year tenure in Hadapsar, Pune, he engaged in projects that utilized Natural Language Processing (NLP), Computer Vision, and Data Mining. His contributions focused on advancing research methodologies and developing innovative solutions.
Internship Experience
Abhay has gained valuable experience through various internships. He served as a Summer Research Intern at the Indian Institute of Technology Gandhinagar in 2018 for two months. Additionally, he interned at Indian Oil Corporation Limited in 2017 for one month. These roles provided him with practical exposure to research and industry practices.
Educational Background
Abhay completed his Bachelor of Technology in Electrical Engineering at NIT Silchar from 2015 to 2019. He also achieved primary education at Sri Sathya Sai Vidya Vihar from 2015 to 2019. His educational background laid the foundation for his expertise in data science and engineering principles.
Skills and Areas of Expertise
Abhay is skilled in applying Large Language Models (LLMs) and Machine Learning algorithms to address challenges in Telecom Analytics and Fraud Detection. He is eager to learn new technologies and techniques, emphasizing collaboration with diverse teams and stakeholders to solve real-world problems through data science.