Data Scientist I
About The Position
A Bachelor's Degree in data science, statistics, bioinformatics, analytics, or similar field and two years of experience; Master's Degree in data science, statistics, bioinformatics, analytics, or similar field. Essential Functions; 1. Design, implement, and maintain scalable data ingestion and processing pipelines supporting the NeuroEnclave within UF’s HIPAA-aligned computing environment. 2. Develop and maintain data validation, profiling, and quality control workflows to ensure data integrity, provenance, and reproducibility across datasets. 3. Engineer and optimize high-performance data workflows for large-scale biomedical datasets using Python-based tools and parallel computing frameworks. 4. Standardize and harmonize heterogeneous data formats to support integrated analytics, AI/ML workflows, and cross-dataset interoperability. 5. Implement technical controls supporting IRB-, HIPAA-, and NIH-compliant data access, including containerized environments, access controls, and audit-ready workflows.
Requirements
- A Bachelor's Degree in data science, statistics, bioinformatics, analytics, or similar field and two years of experience
- Master's Degree in data science, statistics, bioinformatics, analytics, or similar field
Nice To Haves
- 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.
Responsibilities
- 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.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Number of Employees
1-10 employees
