Arunit M.
About Arunit M.
Arunit M. is a Machine Learning Engineer at Zest AI in New York, with extensive experience in machine learning and data science from roles at Columbia Business School, Guidewire Software, and international internships in Singapore.
Current Position at Zest AI
Arunit M. holds the position of Machine Learning Engineer at Zest AI, located in New York, United States. In this role, he focuses on deploying machine learning solutions to address real-world challenges, leveraging his extensive background in data science and machine learning.
Experience at Columbia Business School
Arunit M. has multiple tenures at Columbia Business School in New York. From 2022 to 2023, he served as a Research Assistant in Machine Learning (Computer Vision) for six months. During the same period, he also worked as a Student Researcher in Machine Learning (Natural Language Processing) for five months. In these roles, he tackled various projects involving state-of-the-art machine learning techniques in both computer vision and natural language processing.
Educational Background and Expertise
Arunit M. completed his Master of Science (MS) in Data Science from Columbia University in New York, between 2021 and 2022. Prior to this, he earned a Bachelor of Technology (BTech) in Electronics and Communication Engineering from Vellore Institute of Technology from 2017 to 2021. His education has built a strong foundation in data science, machine learning, and engineering.
Previous Industry Experience
Arunit M. has accumulated diverse industry experience through multiple internships. In 2022, he interned as a Machine Learning Engineer at Guidewire Software and as a Research Assistant in Data Science at Columbia University in New York. Additionally, in 2019, he completed academic internships in Big Data Analytics at Hewlett Packard Enterprise and Machine Learning at the National University of Singapore, both in Singapore.
Contributions to Open-Source Projects
Arunit M. has made contributions to open-source projects on GitHub, emphasizing his skills and expertise in machine learning and data science. His active participation in the open-source community demonstrates a commitment to advancing the field and sharing knowledge with peers.