Eli Samuelson
About Eli Samuelson
Eli Samuelson is a Software Engineer with a background in Cartography and GIS. He has experience working at the FDA and Naval Systems, Inc., and has developed various software models using programming languages such as C and Python.
Work at Naval Systems
Eli Samuelson has been employed at Naval Systems, Inc. as a Software Engineer since 2021. His role involves developing software solutions that support various projects within the organization. Located in Lexington Park, Maryland, Samuelson contributes to the company's mission through his technical expertise and problem-solving skills.
Education and Expertise
Eli Samuelson holds a Master’s of Science in Cartography and GIS from the University of Wisconsin-Madison, which he completed from 2021 to 2022. He also earned a Bachelor's degree in Mathematics from The College of Wooster, graduating in 2020. Additionally, he studied abroad at Victoria University of Wellington, achieving another Bachelor's degree in 2018. His educational background provides a strong foundation in data analysis and software development.
Professional Experience at FDA
In 2019, Eli Samuelson worked as an ORISE Fellow at the FDA for two months in White Oak, Maryland. During this time, he developed a Latent Class Model package using C and Python, showcasing his programming skills and ability to work on complex data modeling projects.
Previous Roles and Skills Development
Eli Samuelson has gained diverse professional experience through various roles. He worked as a Retail Associate at REI for three months in 2020, where he developed customer service skills. Additionally, he served as a lifeguard at Twinbrook Swimming Pool, which helped him acquire skills in job maintenance and customer interaction.
Academic Projects and Research
Samuelson completed a Senior Thesis that involved modeling NCAA Division I Coach firings using Logistic Regression and Random Forest techniques. This project utilized tools such as Excel, R, and Python, demonstrating his analytical capabilities and proficiency in statistical modeling.