Teaching and Learning with Technology (TLT) is seeking a data scientist to assist in our growing efforts to use data to support teaching and learning across Penn State. We seek a talented and motivated individual to advance data science initiatives within the University. The successful candidate will join a fast-paced, diverse team of data scientists, application developers, and researchers that work collaboratively on research projects. The successful candidate will be responsible for retrieving and organizing institutional data from a variety of sources and performing various data science techniques ranging from data wrangling, exploratory data analysis, supervised and unsupervised machine learning, natural language processing, and other data science methods to generate insights, move insights into action, and take insights to scale across Penn State. Being housed in TLT this individual will: Liaison with other groups engaged with data science projects, ranging from university-wide efforts related to business intelligence and data science, to experimental, faculty-driven analytics efforts. Contribute actionable insights and findings to various end users, such as teachers, administrators, instructional designers, and students. Be encouraged to publish and share his/her work in journals, conferences, and associations. This job will be filled as a level 2, or level 3, depending upon the successful candidate's competencies, education, and experience. Typically requires a Bachelor's degree or higher in an Engineering or Science discipline or higher plus two years of related experience, or an equivalent combination of education and experience for a level 2. Additional experience and/or education and competencies are required for higher level jobs. The desired candidate will have a strong academic background (Master’s or Ph.D. preferred) that includes work in a computationally intensive scientific field, statistics and/or data science. The successful candidate will be able to extract, validate, analyze, and present data in effective graphical and written format as needed, for publications, proposals, and institutional reports. The successful candidates will have expertise in R, Python, databases, high performance computing and distributed computing.
These salary bands have been established to provide salary guidelines for staff positions.