Christina Knudson

Christina Knudson, Ph.D. has a diverse work experience in roles related to data science and statistics. Christina is currently working as a Lead Data Scientist at CleanChoice Energy. Prior to this, they worked as a Data Scientist where they implemented and developed statistical methods for real-world applications, and also gained experience as an R package developer and YouTube educator.

Dr. Knudson also has a strong academic background. Christina served as an Associate Professor and Assistant Professor of Statistics at the University of St. Thomas, where they designed and delivered courses in various statistical topics, supervised student research, and trained students in R. Additionally, they worked as a Visiting Assistant Professor at Macalester College, teaching classes on statistical modeling and probability, and leading statistical consulting with undergraduate students.

During their time as a Doctoral Candidate, Instructor, and Statistical Consultant at the University of Minnesota, Dr. Knudson conducted research for their dissertation and developed the widely-used R package glmm. Christina also provided statistical consulting services to researchers and collaborated with researchers in the UMN College of Veterinary Science, resulting in peer-reviewed publications.

Early in their career, Dr. Knudson worked as a Summer Biostatistics Intern at the National Institutes of Health, collaborating on the development of a new technique for analyzing genome-wide association data.

Overall, Christina Knudson, Ph.D. has a strong background in data science and statistics, with experience in research, teaching, and consulting.

Christina Knudson, Ph.D. holds a Bachelor of Arts degree in Mathematics from Carleton College, which they earned from 2005 to 2009. Christina later pursued a Ph.D. in Statistics from the University of Minnesota, completing their studies between 2009 and 2016. Additionally, they have obtained several certifications in programming and data science from Coursera in 2022, including "Programming for Everybody (Getting Started with Python)," "Python Data Structures," "SQL for Data Science," and "Using Databases with Python."