| Job Description: |
The Data Management Analyst supports the PRISMA-P Lab within the University of Florida’s Intelligent Clinical Care Center (IC3). This position is a technical data role and a core member of the lab’s data team, responsible for the development, implementation, and operationalization of the NeuroEnclave—a secure, HIPAA-aligned, multimodal neuroscience data repository.
The incumbent designs and maintains scalable, compliant data infrastructure and pipelines supporting integrated analysis of heterogeneous neuroscience datasets, including de-identified EHR data, neuroimaging, digital pathology, electrophysiology, and public neuroscience datasets. The position collaborates closely with data scientists, UF Integrated Data Repository (IDR), Research Computing, and governance teams to ensure reproducible, AI-ready, and regulation-compliant data workflows.
- Design, implement, and maintain scalable data ingestion and processing pipelines supporting the NeuroEnclave within UF’s HIPAA-aligned computing environment.
- Develop and maintain data validation, profiling, and quality control workflows to ensure data integrity, provenance, and reproducibility across datasets.
- Engineer and optimize high-performance data workflows for large-scale biomedical datasets using Python-based tools and parallel computing frameworks.
- Standardize and harmonize heterogeneous data formats to support integrated analytics, AI/ML workflows, and cross-dataset interoperability.
- Implement technical controls supporting IRB-, HIPAA-, and NIH-compliant data access, including containerized environments, access controls, and audit-ready workflows.
- Provide technical support and consultation to faculty, trainees, and research teams using NeuroEnclave resources.
- Assist with onboarding and integration of new internal and publicly available neuroscience datasets.
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| Preferred: |
- Experience working with clinical or biomedical research data.
- Familiarity with high-performance computing (HPC) or secure research computing environments.
- Experience with parallel computing frameworks (e.g., Dask or similar).
- Knowledge of data security, privacy, and compliance considerations (HIPAA, IRB, NIH Data Management & Sharing requirements).
- Experience supporting data infrastructure for AI/ML or advanced analytics.
- Prior experience in a research or academic data environment.
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