Eun Jee Lee
About Eun Jee Lee
Eun Jee Lee is a Technical Lead at Kensho Technologies, where she has worked since 2021. She holds a PhD in Computational and Applied Mathematics from Princeton University and has previous experience as a Machine Learning Engineer at Kensho, as well as internships at HGST, Facebook, and Forensiq.
Work at Kensho Technologies
Eun Jee Lee has been employed at Kensho Technologies since 2021, where she holds the position of Technical Lead. In this role, she oversees technical projects and leads a team of engineers to develop advanced analytical tools. Prior to her current role, she worked as a Machine Learning Engineer at Kensho from 2018 to 2021, contributing to the development of machine learning models and algorithms that enhance data analysis capabilities.
Education and Expertise
Eun Jee Lee earned her Doctor of Philosophy (PhD) in Computational and Applied Mathematics from Princeton University, where she studied from 2013 to 2018. She also holds a Bachelor of Science (BS) degree in Electrical Engineering from the California Institute of Technology, completing her studies there from 2010 to 2013. Her educational background provides her with a strong foundation in mathematical modeling and engineering principles.
Internship Experience
Eun Jee Lee has gained valuable experience through various internships. In 2013, she interned at HGST, a Western Digital company, for four months in the San Francisco Bay Area. She also completed a research internship at Forensiq in 2015 for one month in the Greater New York City Area. Additionally, she worked as a research intern at Facebook in 2017 for three months in Menlo Park, California. These internships contributed to her technical skills and industry knowledge.
Background
Eun Jee Lee has a diverse background in technical roles within the technology sector. Her career began with internships that provided foundational experience in research and development. Following her academic achievements, she transitioned to a full-time role at Kensho Technologies, where she has continued to advance her career in machine learning and technical leadership.