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Evidence Synthesis Information Scientist

Job in Blacksburg, Montgomery County, Virginia, 24062, USA
Listing for: Digital Library Federation
Full Time position
Listed on 2025-12-17
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist
Salary/Wage Range or Industry Benchmark: 65000 USD Yearly USD 65000.00 YEAR
Job Description & How to Apply Below

Minimum Compensation in Local Currency: $65,000 minimum dependent on qualifications and experience

Maximum Compensation in Local Currency: $65,000 minimum dependent on qualifications and experience

Hourly or Salary? Salary

Description

Job Description: The Evidence Synthesis Information Scientist, reporting to the Assistant Director, Evidence Synthesis Services, will join the collaborative Evidence Synthesis Services team in supporting evidence synthesis research at Virginia Tech for Blacksburg, Roanoke, the National Capital Region, and other university locations and affiliates. The successful candidate will be an ambassador for high-quality evidence synthesis at Virginia Tech; as an expert in search techniques and synthesis methods such as systematic reviews;

provide guidelines-based consultation, outreach, live and asynchronous training, and additional support for systematic reviews and other topics related to evidence synthesis; explore emerging tools, resources, and methods for evidence synthesis; supervise student assistants; serve as subject area liaison to one or more departments, institutes, or program areas; and contribute to supporting the Virginia Tech community in adoption of open and collaborative research practices.

Participate in serving on institutional or professional committees, and demonstrating a commitment to team efforts, service excellence, and Virginia Tech’s Principles of Community.

Required Qualifications:
  • Masters degree from an ALA-accredited graduate program; OR an advanced degree in a position-related field, such as: data science, epidemiology, health sciences, life sciences, social sciences, public health, statistics, agricultural science, environmental science, engineering, or other related fields
  • Demonstrated experience leading systematic review search strategy development, implementation, and documentation
  • Demonstrated experience conducting systematic review searches in databases such as MEDLINE/Pub Med, CAB Abstracts, Scopus; other databases via platforms such as EBSCOhost, Pro Quest, Web of Science
  • Demonstrated experience using and supporting others in evidence synthesis search methodologies, guidelines, and standards such as those recommended by Cochrane, Campbell, the Collaboration for Environmental Evidence; PRISMA, MECCIR, ROSES; etc.
  • Demonstrated experience providing reference or research assistance and instruction/training in an academic, research, or clinical environment
  • Demonstrated experience in outreach, relationship building, and collaboration with a variety of groups such as faculty, students, or vendors
  • Demonstrated experience designing, planning, implementing, and maintaining complex projects
  • Demonstrated experience collaborating with colleagues to problem-solve and share knowledge, with a commitment to team efforts and service excellence
  • Demonstrated ability to effectively understand and communicate complex ideas to novice and scientific/technical audiences
  • Excellent writing and communication skills, including experience with proofreading publication manuscripts and following a variety of style guides
  • Preferred Qualifications:
  • Demonstrated experience peer reviewing systematic review search strategies
  • Demonstrated experience using and/or training others in evidence synthesis project management tools, such as:
    Covidence, Distiller

    SR, Rayyan, or others
  • Demonstrated experience providing support or instruction for developing and refining research scope; critical appraisal of primary research; systematic data extraction or coding; approaches to synthesizing qualitative evidence; and/or archiving supplemental material
  • Demonstrated experience with conducting and/or interpreting primary research
  • Demonstrated experience managing and/or analyzing data
  • Demonstrated experience in using and/or training others in text or data mining, machine learning, language models, or other AI tools for evidence synthesis
  • Demonstrated experience supervising students and/or staff
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