Collaborate with assigned departments to provide actionable data-driven insights through research and analysis of data sources and development of statistical mathematical and predictive models. Support departments to make informed data-driven decisions to meet quality and business objectives. Understand all phases of the analytic process including data collection preparation modeling evaluation and deployment. Explore and examine data from multiple disparate sources in order to identify provide reporting on and analyze trends in the data as well as regular reporting for assigned departments. Establish links across existing data sources and find new interesting data correlations. Develop statistical mathematical and predictive models using strategic business understanding to build the algorithms necessary to ask the right questions and find the right answers. Stay appraised of all assigned initiatives providing reporting and analytics that will allow the group to make informed data-driven decisions to meet business objectives. Visualize and report data findings creatively in a variety of visual formats that appropriately provides insights to the stakeholders. Under general supervision formulates and defines analytic scope and objectives through research and fact-finding. Is able to answer defined questions about health system functions/operations/populations using appropriate statistical techniques on available data. Drives the collection of new data and the refinement of existing data for new purposes. Analyze and interpret the results of experiments to create cost effective and process-efficient alternatives enhancements or modification. Competent to work on most phases of data analysis and associated programming activities.

The ideal candidate will be able to:
•\tDevelop and implement machine learning models using structured and unstructured healthcare data from EPIC and other sources.
•\tDesign, test, and deploy AI-driven decision support tools within clinical workflows.
•\tEngineer data pipelines for large-scale clinical datasets, ensuring efficiency and security in handling sensitive health information.
•\tIntegrate AI solutions with EPIC and cognitive computing platforms to optimize care delivery and reduce clinician burden.
•\tEvaluate model performance and interpret findings to ensure ethical, equitable, and generalizable AI applications in healthcare.
•\tCollaborate with interdisciplinary teams (physicians, informaticians, engineers) to align AI solutions with clinical and operational priorities.
• Document and publish research findings in peer-reviewed journals and present at conferences.

The ideal candidate will have:
•\tPhD or equivalent experience in a relevant discipline.
•\tExperience working with healthcare data.
•\tStrong proficiency in machine learning, deep learning, and data science techniques, particularly in healthcare applications.
•\tExpertise in Python, R, SQL, and experience with cloud computing environments (e.g., AWS, GCP, Azure).
•\tExperience with data engineering, model deployment, and MLOps best practices.
•\tDemonstrated ability to translate research into real-world implementations in healthcare settings.
•\tStrong communication skills with the ability to work effectively in a cross-functional, translational research environment.
•\tExperience with federated learning, reinforcement learning, or generative AI in clinical applications.
•\tProficiency in FHIR, HL7, and healthcare interoperability standards.
•\tFamiliarity with NLP and computer vision models for healthcare documentation and imaging applications.
•\tPrior experience in AI model validation, bias mitigation, and explainability in healthcare AI.

Understands all phases of the data science process including opportunity analysis, intervention design, intervention implementation and evaluation.  The data science process is supported by data collection, preparation, modeling, evaluation, and deployment.Under general supervision, formulates and defines analytic scope and objectives through research and fact-finding. Competent to work on most phases of data analysis and associated programming activities.

Position Compensation Range: $89,523.20 - $143,228.80 Annual

MINIMUM REQUIREMENTS

Education: Master’s Degree required.
Experience: 3-5 years relevant experience.
Licensure: None required

PHYSICAL DEMANDS

This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.

The University of Virginia, including the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff.  We believe diversity is excellence expressing itself through every person's perspectives and lived experiences.  We are equal opportunity employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex, pregnancy, sexual orientation, veteran or military status, and family medical or genetic information.