Aaron Lichtner
About Aaron Lichtner
Aaron Lichtner is a Principal Data Scientist currently working at Shelf Engine in Seattle, Washington. He has extensive experience in data science and research, having held various roles in organizations such as Nordstrom, Galvanize Inc, and the University of Washington.
Current Role at Shelf Engine
Aaron Lichtner currently serves as Principal Data Scientist at Shelf Engine, a position he has held since 2022. In this role, he focuses on leveraging data science techniques to optimize operations and enhance decision-making processes within the organization. His responsibilities include developing predictive models and conducting data analysis to support business objectives.
Previous Experience in Data Science
Prior to his current position, Aaron Lichtner worked at Nordstrom in various data science roles from 2016 to 2021, including Senior Data Scientist and Data Scientist II. His experience at Nordstrom involved applying machine learning and analytics to improve customer experiences and operational efficiencies. He also served as a Data Science Fellow at Galvanize Inc from 2016 to 2021, where he honed his skills in data visualization and modeling.
Educational Background
Aaron Lichtner holds a Doctor of Philosophy (PhD) in Materials Science from the University of Washington, which he completed from 2010 to 2015. He also earned a Master's degree in the same field at the same institution from 2010 to 2012. Earlier, he obtained a Bachelor of Science in Materials Engineering from California Polytechnic State University-San Luis Obispo, where he studied from 2005 to 2009.
Research and Publications
During his graduate studies, Aaron Lichtner authored multiple papers and presented at international conferences, focusing on topics such as freeze-casting and solid-oxide fuel cells. His research contributions reflect his strong background in analytics and data visualization, showcasing his ability to tackle complex scientific problems.
Teaching and Mentorship Experience
Aaron Lichtner has experience in academia, having served as a Teaching Assistant at the University of Washington from 2010 to 2011. In this role, he supported faculty in delivering course content and assisted students in understanding complex materials. His background in education complements his professional experience in data science and research.