|Date Posted||January 15, 2021|
|Education Requirements||ALA-accredited master’s degree in Library or Information Science or advanced degree in computer science, a quantitative social science, or related field.|
|Minimum Compensation in Local Currency||60,000|
|Maximum Compensation in Local Currency||70,000|
|Hourly or Salary?||Salary|
The Applied Data Science Services Librarian provides robust data science support services and evidence-based pedagogical opportunities in computational methods for Penn community members across the disciplines and with varying degrees of technical and methodological experience. The Librarian designs and delivers a sustainable, scalable research support program and a range of instructional support materials for established and emerging data science tools and methodologies for such as web scraping, data mining, and machine learning, as well as programming and scripting languages such as Python and R for research, analysis, and data visualization and communication. Along with colleagues in Research Data and Digital Scholarship, the position is responsible for providing instruction and outreach to faculty, students, and interdisciplinary campus groups, supporting both individual and team or lab data-driven research and scholarship.
The Research Data and Digital Scholarship team currently boasts expertise in text mining, Geographic Information Systems and spatial visualization, data curation, topic modeling, network analysis, data stewardship, public digital humanities, research data management and FAIR data, and research communication. The team provides training in digital literacies, ethics, and methods to students, faculty, and clinicians; collaborates and advises on the design, creation, dissemination, and preservation of digital scholarship projects. The Applied Data Science Librarian will unique but complementary strengths, including but not limited to in-depth knowledge of programming and scripting languages and libraries for computational research at all levels to an engaged team and play a critical role in the disciplinary expansion of the team’s deep expertise in the humanities and humanistic social sciences and experience in meeting researcher needs to the quantitative social sciences, the biomedical sciences, and beyond.
- ALA-accredited master’s degree in Library or Information Science or advanced degree in computer science, a quantitative social science, or related field.
- Ability to use a variety of tools to extract and manipulate data from various sources (such as relational databases, web services and APIs).
- Demonstrated advanced data skills, including data cleaning/wrangling/normalization, using regular expressions, and web scraping.
- Familiarity with one or more data visualization tools or programming libraries (e.g., Tableau, d3.js, ggplot2, R Studio)
- Demonstrated experience with data analysis tools such as R, STATA, SPSS, and SAS.
- Experience with the creation, dissemination, and teaching of interactive instructional materials via Jupyter Notebooks and containerized environments
- Interest in the ethical procurement, structuring, documenting, and interpreting of data for AI/ML
- Interest in algorithmic bias and the responsible use of data science and machine learning for research and scholarship