Mukesh Gadupudi
About Mukesh Gadupudi
Mukesh Gadupudi is a Senior Data Scientist with a diverse background in software engineering and data science across various companies. He has expertise in Python applications, statistical analysis, and deep learning, and has worked in both startups and multinational corporations.
Current Role at Imperial Dade
Mukesh Gadupudi serves as a Senior Data Scientist at Imperial Dade, a position he has held since 2023. In this role, he applies his expertise in data science to support the company’s objectives in the New York City Metropolitan Area. His responsibilities likely include developing data-driven solutions and leveraging advanced analytical techniques to enhance operational efficiency.
Previous Experience in Data Science
Prior to his current role, Mukesh worked as a Senior Data Scientist at Zeus Living from 2022 to 2023. He also held the position of Data Scientist at the same company from 2021 to 2022. His work at Zeus Living involved utilizing data science methodologies to drive insights and improve business processes across their operations in Singapore and San Francisco.
Experience in Software Engineering
Mukesh has a solid foundation in software engineering, having worked as a Software Engineer at Goldman Sachs from 2020 to 2021. His role focused on Commodities Trading and Sales Technology in Singapore. Additionally, he completed software engineering internships at TechMojo Solutions in 2017 and Visa in 2019, where he gained practical experience in software development.
Educational Background
Mukesh studied Computer Science at the National University of Singapore, where he earned a Bachelor of Science (BS) degree. He also participated in the NUS Overseas Colleges program, achieving NOC Israel, Batch 15. His educational background provided him with a strong foundation in computer science principles and practices.
Technical Skills and Expertise
Mukesh possesses a range of technical skills, including proficiency in programming languages such as Python, Java, Go, and SQL. He has expertise in developing multiprocessing Python applications to tackle complex architectural challenges and ensure scalability. His knowledge extends to statistical analysis, large language models (LLMs), geospatial data science, and deep learning.