Wendy Klusendorf is a seasoned professional with over 20 years of experience in the manufacturing sector, specializing in supply chain management and data analysis within the consumer packaged goods industry. Currently serving as an Instructor in the Master of Science in Applied Data Science program...
Wendy Klusendorf is a seasoned professional with over 20 years of experience in the manufacturing sector, specializing in supply chain management and data analysis within the consumer packaged goods industry. Currently serving as an Instructor in the Master of Science in Applied Data Science program at the University of Chicago, Wendy leverages her extensive background to equip students with the analytical skills necessary for today’s data-driven landscape. Her role involves teaching critical concepts in statistics, particularly through the lens of R programming, where she has been instrumental in guiding students through the complexities of data analysis and interpretation.
In addition to her teaching responsibilities, Wendy has taken on the role of Capstone project advisor since 2021, where she mentors students as they apply their learning to real-world challenges. Her expertise in continuous improvement and lean manufacturing principles enriches the curriculum, allowing students to understand the practical implications of data science in optimizing supply chain processes. Wendy's previous experience as a teaching assistant for courses such as Time Series in R and Data Mining in SAS further underscores her proficiency in statistical methodologies and data analytics.
Wendy's commitment to fostering a collaborative learning environment is evident in her hands-on approach, encouraging students to engage with data through projects that reflect current industry trends. By integrating her professional insights with academic rigor, she prepares her students not only to excel in their studies but also to thrive in their future careers in data science and analytics. Her unique blend of industry experience and academic expertise positions her as a valuable asset to the University of Chicago and the broader field of applied data science.
