Data Management and Curation Consultant

Job Description

The Data Management and Curation Consultant provides expert guidance to researchers and students on data management activities across the research enterprise at Virginia Tech. This position has responsibility for providing advice on data management planning data curation and data sharing. Using best practices and emerging standards they will design implement and evaluate data curation preservation and transformation strategies to research data stewarded and preserved by the Library. They will consult with researchers on their data management needs including research using AI applications and will provide specialized scholarly services to research teams seeking federal and private funding. They will also engage in scholarly activities related to these responsibilities.

Required Qualifications

-A terminal degree in a field related to the job duties such as a Masters in Library and/or Information Science (MLS MLIS MIS etc) from an ALA-accredited graduate program
-Demonstrated experience in service provision/working with clients
-Coursework or experience using data in a disciplinary research setting e.g. agriculture environmental science etc
-Demonstrated experience in public presentation oral and written communication
-Problem solving skills and a demonstrated ability to work independently
-Demonstrated experience reading executing and troubleshooting code
-Demonstrated experience in any of the following: research data documentation research data archiving research data publication secondary use of research data

Preferred Qualifications

-An active research agenda demonstrated through published scholarly work
-Demonstrated experience in working in a collaborative team-based environment
-Demonstrated experience in development and/or delivery of guidance or training to faculty or students
-Demonstrated experience with repository operation and/or administration
-Demonstrated experience in metadata creation and management
-Demonstrated experience in service program planning and development
-Demonstrated experience in data management planning and writing/reviewing of data management plans for funding proposals
-Demonstrated experience in programming e.g. in Python R SQL
-Demonstrated experience with AI machine learning and/or large language model (LLM) applications
-Coursework or experience using data in an academic research setting

Overtime Status

Exempt: Not eligible for overtime

Appointment Type

Regular-Continued Appointment Track/Assistant Professor

Salary Information

$63000 minimum dependent on qualifications and experience

Hours per week

40

Review Date

9/16/26

Additional Information

The application package needs to include a resume cover letter addressing the candidates experience with the responsibilities associated with the position and the required and preferred qualifications and the names of three(3) references and their contact information.

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its mottoUt Prosim(That I May Serve) Virginia Tech pushes the boundaries of knowledge by taking a hands-on transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world Virginia Tech is aninclusive communitydedicated to knowledge discovery and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36000 undergraduate graduate and professional students in eightundergraduate colleges aschool of medicine aveterinary medicinecollegeGraduate School andHonors College.The university has a significant presence across Virginia including Blacksburg the greater Washington D.C. area the Health Sciences and Technology Campus in Roanoke sites in Newport News and Richmond and numerousExtension officesandresearch institutes.A leading global research institution Virginia Tech conducts more than $650 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance. These valuable contributions to university shared governance provide important representation and perspective along with opportunities for unique and impactful professional development.