Lauren Saum
About Lauren Saum
Lauren Saum is a Data Engineer with five years of experience at Civitas Learning in the Austin, Texas area. She has a background in education and data science, having worked as a teacher and held various roles at Galvanize Inc.
Work at Civitas Learning
Lauren Saum has been employed at Civitas Learning as a Data Engineer since 2019. In this role, she contributes to data analysis and engineering projects aimed at enhancing educational outcomes. Her work focuses on leveraging data to support institutional decision-making and improve student success. Civitas Learning is known for its commitment to using data insights to drive positive changes in higher education.
Previous Experience in Education and Data Science
Before joining Civitas Learning, Lauren Saum worked in various roles that combined education and data science. She served as an Instructor at Hello World for 10 months in 2019, where she taught programming and data skills to students in Austin, Texas. Additionally, she completed a Data Science Residency at Galvanize Inc, where she engaged in intensive training and projects related to data science. Her experience at Galvanize included both remote and in-person roles.
Teaching Background
Lauren Saum has a solid foundation in education, having worked as a Teacher at Casis Elementary within the Austin Independent School District from 2012 to 2018. During her six years in this role, she focused on early childhood education, developing skills in curriculum design and classroom management. This experience provided her with insights into the educational system and the importance of data in improving teaching methods.
Education and Expertise
Lauren Saum earned her Bachelor's degree in Early Childhood Education and Teaching from The University of Texas at Austin, where she studied from 2007 to 2011. This educational background laid the groundwork for her career in teaching and later in data engineering. Her academic training has equipped her with the knowledge and skills necessary to bridge the gap between education and data analysis.