The Claude Moore Health Sciences Library seeks a service-oriented Research Data Associate or Research Data Specialist to support faculty, staff, and student researchers by providing consultations and training on applied research data analysis across the data lifecycle. Areas of support include cleaning and manipulating data, experimental design, and statistical analysis. This position will also communicate methods and results, through scientific writing and data visualization design.
The Research Data Associate or Research Data Specialist will guide researchers at all proficiency levels through the processes and tools needed to accomplish their data goals. As a member of Research and Data Services (RDAS), the Associate/Specialist will partner with RDAS colleagues to provide expert research data support through multiple areas of the research lifecycle. This position must stay up to date on emerging data science approaches and anticipated research data needs, collaborating with RDAS team members to review and develop services. They will also work with stakeholders across the institution to contribute to university-wide data-related initiatives.
The Claude Moore Health Sciences Library has made a commitment to promote diversity and inclusivity among our collections and services. We are committed to creating a more just, inclusive, diverse, equitable, and accessible environment for our employees and those whom we serve. We seek candidates whose work and/or service demonstrates their proven commitment to these principles.
JOB RESPONSIBILITIES
- Consults on research data questions and devises customized technical and/or programming solutions for data collection, manipulation, analysis, and visualization.
- Develops and delivers educational content, including live workshops and asynchronous training materials such as guides and tutorials.
- Leads library efforts to create an educational program of data science and statistical topics.
- Writes and delivers customized data science and/or statistical workshops for groups in the Schools and Health System.
- Conducts independent exploration and testing of new programming tools and technologies.
- Seeks educational opportunities and professional development activities regarding new data science and statistical methods and techniques.
- Works with other members of the RDAS team to build and support research data management services around open science and research workflow topics such as rigor and reproducibility and data sharing.
- Engages with other data service providers at the University of Virginia and in the surrounding community and collaborate to foster mutually beneficial partnerships.
MINIMUM REQUIREMENTS
Research Data Associate
Education: Master’s or Doctoral degree in specific academic discipline; Bachelor’s degree with appropriate experience.
Experience: In lieu of Master’s or Doctoral degree, Bachelor’s degree with 8 years of information technology experience or bachelor’s degree with 8 years of non-IT experience in specific relevant disciple.
Anticipated Hiring Range: $55,000 – $65,000, commensurate with education and experience.
Research Data Specialist
Education: Master’s or Doctoral degree in relevant academic discipline
Experience: At least 4 years of relevant experience integrating both the academic discipline and information technology
Anticipated Hiring Range: $70,000 – $84,000, commensurate with education and experience.
PREFERRED QUALIFICATIONS
- Excellent communication and presentation skills.
- Proficiency with R and/or Python programming languages.
- Experience performing statistical inference, such as hypothesis testing, linear models/regression, generalized linear models, or mixed-effect/multilevel models.
- Experience providing research services in an academic setting.
- Experience working with the Tidyverse family of functions in R or pandas in Python.
- Familiarity with health sciences research and data.
- Desire to provide highly responsive, user-centered services.
- Interest in providing instruction, both formal and informal, to varying audiences and skill levels
- Strong technical skills and problem-solving abilities related to data collection, cleaning, and analysis.
- Demonstrated ability to manage multiple projects and to work independently and on teams.