Develop strong working relationships with faculty, staff, and students who use (or support the use of) quantitative and qualitative data in their research, teaching, and scholarship. Provide expert instruction to students, faculty, and staff regarding the discovery, acquisition, management, manipulation, interpretation, analysis, and visualization of data (e.g. infographics, charts, maps, and interactive media) using specialty software and coding languages (e.g. R, Python, Stata, ArcGIS, QGIS); provide expert instruction in specialized methods (e.g. statistical techniques, text/data mining, sentiment analysis, network analysis, GIS). Provide proactive leadership, direction, and vision for the support of digital scholarship and data science research and teaching in the libraries; collaborate with faculty and staff from all Middlebury campuses.