About

Sudarshan Gopalakrishnan is an Analyst at Goldman Sachs with a Bachelor's degree in Electrical Engineering and Computer Science from UC Berkeley College of Engineering. He is interested in cloud infrastructure and computing, optimization, data engineering, and FinTech. Sudarshan has a relevant experience of 1.52 years in the field of Software Engineering and has worked as a Software Engineering Intern at Goldman Sachs, where he modernized Goldman's in-house inventory management system. He uplifted cross-team ETL Pipelines to Python 3.7 and built a CI/CD pipeline for containerized deployment. Sudarshan also built Kubernetes CronJob and pipelined credential delivery to authenticate ETL Endpoints, measure inventory, and deliver results to Elasticsearch Clusters/Kibana dashboards for stakeholders. He devised a health monitoring tool for ETL Endpoints to deliver robust metrics for automation. Sudarshan has also worked as an Undergraduate Student Researcher at UC Berkeley Sutardja Center for Entrepreneurship and Technology - DataX Lab, where he studied stable-matching techniques to achieve optimal team formation for innovation, entrepreneurship, class projects, and industry projects. He developed inferential algorithms to generate high-performance teams based on personality and qualifications and support recommendation engines for networking. Sudarshan won the "Best Paper Award" at the 2021 ICE/IMTC Conference and published two papers with the ICE 2021 IEEE ITMC Conference. Sudarshan's education history includes a Bachelor of Science - BS in Electrical Engineering and Computer Science from the University of California, Berkeley, a Certificate in Entrepreneurship and Technology from the same university, and a High School Diploma from Obra D. Tompkins High School. Sudarshan's tech stack includes Software Engineering, Data Engineering, Infra, Research Scientist, Data Scientist, ETL, CI/CD, Python, Kubernetes, and Elastic Search.