Data Services Librarian

Description

Boston College Libraries are seeking a Data Services Librarian to join our Digital Scholarship Group (DSG). This position is primarily responsible for digital scholarship collaborations and services related to data gathering, manipulation, management, curation, documentation, and data skills training. Such activities include consulting on faculty and student data-driven projects; providing data skills training on data manipulation and management methods, best practices, and tools to faculty and staff; and providing data skills instruction and curriculum consultations for undergraduate and graduate courses. 

As a member of the DSG, the Data Services Librarian collaborates on providing current DS services, designing and implementing new ones, and is a valued voice in DSG strategic planning and goal setting as the group strives to expand its role in BC Libraries and the broader BC community. The collaborative nature of this position extends to working with staff across the Libraries (subject liaison librarians, in particular) and across campus with units such as Research Services to meet faculty and student research data needs.
Hiring Range: $65,800 to $82,250; salary commensurate with relevant experience.

Requirements

A Master’s degree in Library Science or Information Science, or a closely related, data-intensive research field, plus 2-3 years of relevant experience. Demonstrated experience in providing data curation, management, cleaning, and mining services;
Using data and related technologies to support teaching or research;
Working with numeric data in an academic, scientific, or corporate environments
The ability to engage with research across a variety of disciplines and a range of audiences, from undergraduate and graduate students to faculty, instructors, and staff. Excellent written and oral communication skills 

Preferred
Experience working in academic libraries;
Knowledge of data preservation strategies;
Demonstrated experience in
Working with data repository platforms (e.g. Dataverse);
Proving data skills training and classroom instruction (oral, written and video tutorials, etc.);Data/text mining and analysis using coding languages such as Python or R;
Using statistical tools (e.g., SPSS, SAS, Stata)