Overview
On Site
USD 89,523.20 - 143,228.80 per year
Full Time
Skills
Clinical Research
Decision-making
Advanced Analytics
Operational Excellence
Immigration
Survival Analysis
Regulatory Compliance
Data Governance
Privacy
Biostatistics
Epidemiology
Design Of Experiments
Epic
Programming Languages
R
Python
SQL
Statistical Models
Machine Learning (ML)
Data Engineering
Machine Learning Operations (ML Ops)
HL7
Health Care
Artificial Intelligence
Communication
Collaboration
Data Science
Data Collection
Modeling
Evaluation
Supervision
Analytical Skill
Research
Data Analysis
Job Details
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.
The ideal candidate will be able to:
Design, execute, and analyze randomized controlled trials, quasi-experimental studies, and observational research using healthcare data.
Develop and implement machine learning models using structured and unstructured healthcare data from EPIC and other sources.
Apply advanced statistical techniques for causal inference, longitudinal data analysis, and survival analysis to real-world healthcare data.
Engineer data pipelines for large-scale clinical datasets, ensuring efficiency and compliance with data governance and privacy standards.
Integrate AI solutions with EPIC and cognitive computing platforms to optimize care delivery and reduce clinician burden.
Evaluate model performance, interpret findings, and ensure ethical, equitable, and generalizable AI applications in healthcare.
Collaborate with interdisciplinary teams (physicians, informaticians, engineers) to align AI and statistical study designs with clinical and operational priorities.
Publish research findings in peer-reviewed journals and present at conferences, demonstrating methodological transparency and reproducibility.
The ideal candidate will have:
PhD or Masters plus three years experience in biostatistics, epidemiology, health data science, or a related field.
Demonstrated expertise in design of experiments, observational study design, and health services research methodologies.
Experience working with healthcare data, particularly from EHR systems such as EPIC.
Proficiency in statistical software and programming languages (R, Python, SQL).
Strong knowledge of advanced statistical modeling, machine learning, and causal inference techniques.
Experience with data engineering, model deployment, and MLOps best practices.
Familiarity with FHIR, HL7, and healthcare interoperability standards.
Prior experience in AI model validation, bias mitigation, and explainability in healthcare AI.
Strong communication skills and the ability to collaborate in a cross-functional, translational research environment.
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.
This position will not consider candidates who require immigration sponsorship at this time or in the future.
The ideal candidate will be able to:
Design, execute, and analyze randomized controlled trials, quasi-experimental studies, and observational research using healthcare data.
Develop and implement machine learning models using structured and unstructured healthcare data from EPIC and other sources.
Apply advanced statistical techniques for causal inference, longitudinal data analysis, and survival analysis to real-world healthcare data.
Engineer data pipelines for large-scale clinical datasets, ensuring efficiency and compliance with data governance and privacy standards.
Integrate AI solutions with EPIC and cognitive computing platforms to optimize care delivery and reduce clinician burden.
Evaluate model performance, interpret findings, and ensure ethical, equitable, and generalizable AI applications in healthcare.
Collaborate with interdisciplinary teams (physicians, informaticians, engineers) to align AI and statistical study designs with clinical and operational priorities.
Publish research findings in peer-reviewed journals and present at conferences, demonstrating methodological transparency and reproducibility.
The ideal candidate will have:
PhD or Masters plus three years experience in biostatistics, epidemiology, health data science, or a related field.
Demonstrated expertise in design of experiments, observational study design, and health services research methodologies.
Experience working with healthcare data, particularly from EHR systems such as EPIC.
Proficiency in statistical software and programming languages (R, Python, SQL).
Strong knowledge of advanced statistical modeling, machine learning, and causal inference techniques.
Experience with data engineering, model deployment, and MLOps best practices.
Familiarity with FHIR, HL7, and healthcare interoperability standards.
Prior experience in AI model validation, bias mitigation, and explainability in healthcare AI.
Strong 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.
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.