Research Computing Consultant II – Data Science.

About the role

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.

Responsibilities

• Assists faculty, postdoctoral scholars, and graduate students in assessing analytic needs and identifying appropriate quantitative, statistical, and computational approaches suited to their research questions and disciplinary context.
• Provides foundational guidance on model selection, validation strategies, and interpretation of analytical results across diverse research domains including biomedicine, public health, social sciences, and the humanities.
• Guides researchers in evaluating and responsibly adopting AI-enabled tools, including large language models, to enhance their analytical workflows and research practice.
• Aids researchers in structuring, cleaning, and summarizing complex datasets to support exploratory analysis, reporting, and communication of findings.
• Supports implementation of commonly used statistical analyses including regression, mixed-effects, survival, and multivariate approaches using R and Python.
• Contributes to the preparation of methods sections, analytical summaries, and data narratives for research manuscripts and proposals.
• Supports analytical planning related to research proposals.
• Helps develop text and corpus analysis workflows, including data extraction, preprocessing, and quantitative characterization of textual or qualitative data sources.
• Aids project teams in developing reproducible workflows using scripting, version control, and workflow management best practices.
• Troubleshoots routine analytical and methodological challenges, and works closely with senior team members to resolve more complex problems.
• Assists in the design and delivery of introductory workshops and training sessions on applied statistics, data science methods, data visualization, artificial intelligence, reproducible research practices, and HPC usage.
• Develops accessible documentation, tutorials, and practical learning resources for researchers at all career stages.
• Provides accessible consultation and training support.
• Engages departments and interdisciplinary research groups to expand awareness and adoption of research computing and data science services.
• Translates complex statistical and computational concepts into clear, accessible guidance for audiences with diverse technical backgrounds.
• Develops publication-quality data visualizations using R, Python, or comparable tools, with attention to accessibility and clarity.
• Supports development of interactive dashboards and reporting tools to help researchers communicate findings effectively (e.g., Shiny, Dash, or comparable platforms).
• Advices investigators on data organization, storage strategies, and lifecycle management practices appropriate to their discipline and compliance requirements.
• Promotes responsible and compliant use of data science and AI tools in research contexts.
• Promotes documentation and reproducibility as foundational practices across research projects.
• Maintains and actively expands knowledge of applied statistical methods, data science methodologies, research computing technologies, and emerging developments in AI as they apply to research practice.
• Serves as a collegial resource to team members and contributes to a collaborative, service-oriented environment.
• Promotes equitable and inclusive access to research computing resources, statistical consultation, and training across campus communities.

Qualifications

• Master's Degree Required
• One year of experience in applied data science, applied statistics, research computing, or computational research support.
• 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.

Skills

• Strong programming proficiency in R and Python.
• Effective communication skills.
• Workshop hosting experience.
• Genuine enthusiasm for collaborative research.

Benefits

• Flexible schedule.
• Hybrid work arrangement.
• Professional development opportunities.

Pay

Minimum $87,700, maximum $115,000.

Schedule

Full-time, 40 hours per week.

Location

Hanover, NH.