2. Assist study teams in preparing analysis‑ready datasets for downstream statistical analysis

3. Maintain documentation for data dictionaries, extraction logic, and data‑cleaning procedures.

4. Build and maintain internal databases to support operational tracking and reporting.

5. Design and implement automated data pipelines to reduce manual data handling and improve data quality.

6. Develop dashboards and visualizations to help research leadership monitor key performance metrics.

7. Collaborate with research institute staff to translate reporting needs into practical data solutions.

1. Proficiency SQL for querying relational databases.

2. Experience with Python or R for data cleaning, manipulation, and automation.

3. Data documentation practices, including data dictionaries and extraction logic.

4. Familiarity with healthcare data standards or clinical data structures (e.g., EHR data, ICD codes) preferred

5. Experience with business intelligence or data visualization tools such as Power BI preferred.

6. Exposure to ETL/ELT concepts and research data management platforms such as REDCap preferred.

Education and Experience

1. Education: Currently enrolled in an undergraduate or graduate degree program in a relevant field such as biomedical informatics, data science, computer science, public health, statistics, biology, or a related discipline. Completion of at least one year of higher education coursework prior to the internship. Must be returning to at least one additional semester of school following the internship.

2. Licensure: None

3. Certification: None

4. Years of relevant experience: Prior experience in a research, clinical, or academic setting is preferred

5. Years of supervisory experience: None