Research Data & AI Solutions Specialist
About The Position
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.
Requirements
- 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.
Nice To Haves
- 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.
