Research Data & AI Solutions Specialist

The Data Science and AI Research Service is a team within the School of Data Science and Society that supports data intensive and AI enabled research across a broad range of data science and AI domains. The service advances research productivity and innovation by helping research teams design, adopt, and scale software engineering, data engineering, and AI enabled research technologies that align with scholarly goals and best research practices.

The Research Data & AI Solutions Specialist works directly with faculty, research staff, and graduate students to translate research questions and workflows into usable, scalable data and AI research technologies. The role combines solutions development, applied technical expertise, and research partnership to design, prototype, and scale data and AI enabled technologies in support of SDSS faculty research programs. These technologies may include research software tools, analytical and modeling pipelines, automation scripts, dashboards, visualization systems, and AI enabled research assistants.

The role is strongly end user focused, emphasizing co design with researchers, iterative prototyping, usability in real research contexts, and sustained adoption across projects and labs. The position technically enables SDSS faculty research by supporting tool development and data collection to enhance impact of grant applications and implementation of research projects, enabling reuse of shared tools, and connecting research teams to appropriate technical and institutional resources. Minimum Education and Experience Requirements, 3. * Describe a concrete example of a prototype or pilot you helped move towards broader adoption. What decisions did you make to support usability, reuse, or sustainability? (Open Ended Question)

4. • Describe a concrete example of your experience working with user-centered or participatory design approaches in research contexts. (Open Ended Question)
5. • Briefly describe a time you worked with researchers or domain experts to translate an ambiguous research question into a useable data, software, or AI-enabled solution. (Open Ended Question)

Relevant post-Baccalaureate degree required (or foreign degree equivalent); for candidates demonstrating comparable independent research productivity, will accept a relevant Bachelor's degree (or foreign degree equivalent) and 3 or more years of relevant experience in substitution. May require terminal degree and licensure., * Bachelor's degree in Data Science, Computer Science, Information Systems, Information Science, Business Analytics, Business Administration, Economics, Public Health, or related field, or equivalent combination of education and experience., * Experience supporting research software, analytics platforms, data pipelines, or AI-enabled tools in an academic or research setting.

• Experience working directly with faculty or research teams on applied research technology projects.
• Familiarity with user-centered or participatory design approaches in research contexts.
• Experience coordinating pilot projects, prototypes, or shared research tools from concept through adoption.
• Exposure to research data governance or compliance considerations (e.g., sensitive data, regulated environments), with emphasis on enabling not managing research use.
• Experience improving research and research-adjacent workflows through automation, integration, or technical process redesign., 1. * Please select the response below that describes your level of education that best or mostly closely satisfies the education requirements for this position.

• Bachelor's degree in required discipline(s) listed or related field
• Bachelor's degree in any field/discipline
• Master's degree or Doctorate degree in required discipline(s) listed or related field
• Master's degree or Doctorate degree in any field/discipline
• None of the above

2. • Do you have a bachelor's degree in data science, Computer Science, Information Systems, Information Science, Business Analytics, Business Administration, Economics, Public Health, or related field?

Be a Tar Heel! A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation's top public universities. Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional opportunities that span the campus and community. University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select campus events. UNC-Chapel Hill offers full-time employees a comprehensive benefits package, paid leave, and a variety of health, life and retirement plans and additional programs that support a healthy work/life balance. Primary Purpose of Organizational Unit In 2022, UNC Chapel Hill launched the School of Data Science and Society (SDSS), a new school devoted to data science teaching, research, scholarship, service, and creativity. The SDSS vision is to be a leader in shaping the field of data science through an interdisciplinary and rigorous grounding in theory and methods with a human centric approach to the entire data life cycle. The mission of SDSS is to empower a diverse community of faculty conducting research in the fundamentals and/or the applications of data science. The school is training undergraduate, graduate, and professional students to be the next generation of data science leaders with the knowledge and skills to thrive in this data-driven world. The SDSS will serve the state, the nation, and the world through premier data science educational programs and innovative research directed to advancing the public good with human-centric and ethical applications. The core elements of the SDSS include porous borders - leveraging our low-walled collaborative Carolina culture to solve major societal problems. Interdisciplinary research clusters that cross disciplines and school boundaries are a vital element of the school. The SDSS is focused on students and education - the emphasis is not just on data science majors but on all students becoming data literate. The school's culture has an open and transparent structure, governance, and business model.