Jeffrey C. Oliver
Data Science Specialist
University of Arizona
Data science is an interdisciplinary endeavor, merging techniques from computer science and statistics with domain-level concepts to increase discovery through data analytics and visualization. Supporting researchers in their data science needs is a key strategic challenge identified by CNI, especially as training needs in data science often exceed the supply. Capitalizing on domain knowledge and data science expertise in the graduate student population, we created a fellowship program, the Data Science Ambassadors, to connect campus researchers with in-demand data science resources. Graduate students’ ability to “speak the same language” as researchers in their respective domains reduces the communication barrier many researchers face when learning data science applications. The program provides structure, training, and a modest stipend in return for students’ time and expertise. The interdisciplinary nature of data science is reflected in a diverse cohort of students, which includes scholars in the humanities, social sciences, life sciences, and physical sciences. This program has afforded several points of contact and opportunities for campus data science support while fostering the growing network of data science practitioners. In this talk, we discuss the challenges and opportunities of such a program, exemplified by our program at the University of Arizona.
Additional authors: Maliaca Oxnam, Susan J. Miller, Vignesh Subbian