We are seeking a data scientist with deep expertise in statistical design of experiments, observational study design, and clinical research to drive evidence-based decision-making in healthcare. The role combines rigorous research methodology with advanced analytics, machine learning, and AI to evaluate interventions, improve care delivery, and support operational excellence. Candidates should have strong skills in causal inference, experimental design, and healthcare data analysis, with the ability to translate findings into actionable insights and implement high-quality data products.

This position will not consider candidates who require immigration sponsorship at this time or in the future.

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The ideal candidate will be able to:
•\tDesign, execute, and analyze randomized controlled trials, quasi-experimental studies, and observational research using healthcare data.
•\tDevelop and implement machine learning models using structured and unstructured healthcare data from EPIC and other sources.
•\tApply advanced statistical techniques for causal inference, longitudinal data analysis, and survival analysis to real-world healthcare data.
•\tEngineer data pipelines for large-scale clinical datasets, ensuring efficiency and compliance with data governance and privacy standards.
•\tIntegrate AI solutions with EPIC and cognitive computing platforms to optimize care delivery and reduce clinician burden.
•\tEvaluate model performance, interpret findings, and ensure ethical, equitable, and generalizable AI applications in healthcare.
•\tCollaborate with interdisciplinary teams (physicians, informaticians, engineers) to align AI and statistical study designs with clinical and operational priorities.
•\tPublish research findings in peer-reviewed journals and present at conferences, demonstrating methodological transparency and reproducibility.
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The ideal candidate will have:
•\tPhD or Masters plus three years experience in biostatistics, epidemiology, health data science, or a related field.
•\tDemonstrated expertise in design of experiments, observational study design, and health services research methodologies.
•\tExperience working with healthcare data, particularly from EHR systems such as EPIC.
•\tProficiency in statistical software and programming languages (R, Python, SQL).
•\tStrong knowledge of advanced statistical modeling, machine learning, and causal inference techniques.
•\tExperience with data engineering, model deployment, and MLOps best practices.
•\tFamiliarity with FHIR, HL7, and healthcare interoperability standards.
•\tPrior experience in AI model validation, bias mitigation, and explainability in healthcare AI.
•\tStrong communication skills and the ability to collaborate in a cross-functional, translational research environment.

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 is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Click here to read more about UVA’s commitment to non-discrimination and equal opportunity employment.