Research Data Analyst I (25% part-time)

The Department of Medicine is seeking a Research Data Analyst I to support a variety of research projects and clinical trials. The successful candidate will assist with the development and maintenance of study documentation, protocols, and standard operating procedures to ensure compliance with regulatory and institutional requirements.

This role includes responsibilities for data collection, cleaning, validation, and management, as well as performing entry-level statistical analyses to help interpret study results. The analyst will collaborate closely with research staff, investigators, and clinical teams to ensure accurate, high-quality data is available for study reporting, regulatory submissions, and project decision-making.

The position offers an excellent opportunity to gain hands-on experience in research data management, contribute to meaningful clinical research, and develop skills in statistical analysis and regulatory compliance.

This is a 25% part-time limited role which may convert to career.

Hourly range: $31.51-$62.64

Required:

• Demonstrated experience in programming, statistics, data management, and data analysis.
• Bachelor's Degree or equivalent combination of education and experience.
• Up to 1 year of experience in programming, statistics, data management, database design
• Basic knowledge of statistics.
• Knowledge of basic and/or multivariate statistics.
• Knowledge of research design.
• Ability to conceptualize and construct tables and graphs.
• Basic knowledge of statistical and/or medical terminology.
• Basic ability to summarize statistical analyses for collaborator.
• Knowledge of statistical techniques.
• Ability to utilize database management software to run queries and extract data.
• Ability to construct databases.
• Ability to produce visual tools and dashboards that highlight the essential information from a project or study.
• Knowledge of basic office software and applications (e.g., Microsoft Office Suite, Google, Internet search engines, etc.).
• Ability to learn new statistical techniques and to adapt existing code to customize statistical analysis strategies.