Position Purpose
The Research Computing Consultant II (RCCII) - Data Science is a researcher-facing professional who partners with faculty, postdoctoral scholars, and graduate students to support data-intensive research across disciplines. This role applies expertise in applied statistics, artificial intelligence, and data science to help the campus research community, design rigorous analytical workflows, develop publication-quality visualizations, and build reproducible computational practices. The RCCII…
applies methodological knowledge across a broad range of research contexts, spanning biomedical and public health sciences through to the social sciences and humanities.
This is an early-career professional role designed for a curious individual with a foundational background and some experience in applied quantitative research support who is ready to develop their expertise within a collaborative, research-oriented environment. The position reports to the Director of Research Engagement and Data Science and works in close partnership with the Research Cyberinfrastructure and Research Software Engineering teams. Strong programming proficiency in R and Python, effective communication skills, workshop hosting experience, and a genuine enthusiasm for collaborative research are essential to success in this role.
Required Qualifications - Education and Yrs Exp
Master's degree
Required Qualifications - Skills, Knowledge and Abilities
- Master's degree in biostatistics, statistics, data science, epidemiology, computer science, computational science, or a related quantitative discipline.
- Minimum of one year of experience in applied data science, applied statistics, research computing, or computational research support.
- Experience supporting or participating in data-intensive research projects.
- Strong proficiency in both R and Python
- Demonstrated experience with applied statistical modeling, including at minimum regression and mixed-effects frameworks.
- Working knowledge of large language models or AI-assisted tools and their potential applications in research or data science contexts.
- Familiarity with high-performance computing or advanced computational environments.
- Demonstrated ability to communicate quantitative concepts clearly to audiences with diverse technical backgrounds.
- Experience developing or delivering technical training, documentation, or instructional materials.
- Ability to work on campus multiple days per week; this is a hybrid-eligible role requiring consistent in-person presence to support the research community.
