Kessinee C.
About Kessinee C.
Kessinee C. is a Senior Data Scientist at Benson Hill in St. Louis, Missouri, with a strong educational background that includes a PhD in Statistics and an MS in Applied Mathematics. She has extensive research experience in machine learning and graphical models, and has held various positions in academia and industry.
Current Role at Benson Hill
Kessinee C. serves as a Senior Data Scientist at Benson Hill, a position held since 2021. Based in St. Louis, Missouri, Kessinee applies advanced data science techniques to support the company's objectives. The role involves leveraging statistical methods and machine learning to analyze complex datasets, contributing to the development of innovative agricultural solutions.
Education and Expertise
Kessinee C. holds a Doctor of Philosophy (PhD) in Statistics from Kansas State University, completed between 2012 and 2019. Additionally, Kessinee earned a Master of Science (MS) in Applied Mathematics from California State University, Long Beach, from 2010 to 2012. Kessinee also possesses a Bachelor of Business Administration (BBA) in Finance from Mahidol University, obtained from 2003 to 2007. This diverse educational background supports expertise in classical and Bayesian statistics, causal inference, and hierarchical Bayesian methodologies.
Previous Work Experience
Before joining Benson Hill, Kessinee C. worked as a Product Analytics Specialist at Pig Improvement Company (PIC) - North America from 2019 to 2021. Prior to that, Kessinee served as a Graduate Research Assistant and Graduate Teaching Assistant at Kansas State University from 2013 to 2018. These roles involved research and teaching responsibilities, enhancing Kessinee's analytical skills and experience in academia.
Research Experience
Kessinee C. has significant research experience in graphical models and machine learning. This includes interfacing designed experiments with observational studies, showcasing the ability to tackle big-data challenges through interdisciplinary applications. The focus on causal inference and hierarchical Bayesian methodologies further emphasizes Kessinee's analytical capabilities.