This role is part of a growing Research Methods and Data Science team that is actively building shared infrastructure, standards, and workflows. The right candidate brings technical rigor, attention to detail, and a service orientation toward the research teams they support.

2. Extract, query, and join data from primary research sources including the EHR (Epic), REDCap, and Cosmos related to mental health services, patient outcomes, and treatment effectiveness.

3. Compute and recode variables to meet study-specific analytical specifications.

4. Deliver clean, analysis-ready datasets to biostatisticians and study teams, and remain available for follow-up pulls and revisions throughout the study lifecycle.

5. Develop and maintain data documentation including data dictionaries, codebooks, and extraction SOPs.

6. Build and manage REDCap projects, from straightforward data collection instruments to complex longitudinal projects with branching logic and calculated fields.

7. Write reproducible, well-documented code following RMDS shared standards, using version control for all analytical workflows.

8. Support multiple study teams simultaneously across clinical departments, managing priorities and communicating proactively about timelines and constraints.

9. Contribute to the development of RMDS team infrastructure, including shared code libraries, documentation standards, and data preparation workflows.

1. Proficiency in SQL for data querying, joining, and transformation is required.

2. Proficiency in R or Python for data manipulation, recoding, and reproducible workflows is preferred.

3. Experience with version control and reproducible research practices is preferred.

4. Experience building REDCap projects, including instruments, branching logic, and calculated fields is preferred. Training provided for candidates with foundational skills.

5. Familiarity with EHR data structures, particularly Epic, preferred.

6. Experience with research data documentation including data dictionaries and codebooks preferred.

Education and Experience

1. Education: Bachelor's degree required in a quantitative or research-related field such as biomedical informatics, public health, health sciences, statistics, or a related discipline. Master's degree preferred.
2. Years of relevant experience: Minimum two years of experience in data extraction, management, or analysis in a research or clinical setting preferred. Strong new graduate candidates with relevant technical skills will be considered.
3. Experience working in academic medical center or research institute settings preferred.
4. Demonstrated ability to manage multiple priorities and communicate effectively with research teams.
5. Licensure: not applicable
6. Certification: not applicable
7. Years of supervisory experience: not applicable