Biomedical Data Management & Analytics Analyst

UTHealth Houston; Houston (TX); On-site; USD 65,000 - 90,000; Full time

Job summary

UTHealth Houston's McWilliams School of Biomedical Informatics is seeking a data-focused professional to support multiple research projects. You will perform intermediate data creation, management, analysis and troubleshooting using analytical tools and statistical methods.

Join a world-class healthcare research environment. The role emphasizes data quality, collaboration with researchers, and ensuring robust data pipelines.

Qualifications

• Bachelor's Degree in Business, Computer Science, or related field required.
• May substitute required education with equivalent years of experience beyond the minimum education requirement.
• Minimum Experience: 3 years of experience with complex databases.
• May substitute required experience with equivalent years of education beyond the minimum education requirement.
• Physical Requirements: Exerts up to 50 pounds of force occasionally and/or up to 20 pounds frequently and/or up to 10 pounds constantly to move objects.

Responsibilities

• Managing/maintaining data for multiple projects or research efforts.
• Creates, supports, and troubleshoots tools or software used to manage data.
• Develops and maintains quality controls for all research databases.
• Designs database queries and compiles, analyzes, and reports statistical data for research projects.
• Interfaces with vendors and offsite researchers and coordinators.
• Performs other duties as assigned.

Education

Bachelor's Degree in Business, Computer Science, or related field

3 years of experience with complex databases

Job description

UTHealth Houston's McWilliams School of Biomedical Informatics is seeking a data-focused professional to support multiple research projects. You will perform intermediate data creation, management, analysis and troubleshooting using analytical tools and statistical methods.

Join a world-class healthcare research environment. The role emphasizes data quality, collaboration with researchers, and ensuring robust data pipelines.