Overview
On Site
USD 89,523.20 - 143,228.80 per year
Full Time
Skills
Algorithms
Analytics
Reporting
Decision Support
Workflow
Epic
Collaboration
Machine Learning (ML)
Deep Learning
Python
R
SQL
Cloud Computing
Amazon Web Services
Google Cloud Platform
Google Cloud
Microsoft Azure
Data Engineering
Machine Learning Operations (ML Ops)
Communication
Generative Artificial Intelligence (AI)
HL7
Natural Language Processing
Computer Vision
Documentation
Health Care
Artificial Intelligence
Data Science
Data Collection
Modeling
Evaluation
Supervision
Analytical Skill
Research
Data Analysis
Nursing
Science
Military
Job Details
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:
Develop and implement machine learning models using structured and unstructured healthcare data from EPIC and other sources.
Design, test, and deploy AI-driven decision support tools within clinical workflows.
Engineer data pipelines for large-scale clinical datasets, ensuring efficiency and security in handling sensitive health information.
Integrate AI solutions with EPIC and cognitive computing platforms to optimize care delivery and reduce clinician burden.
Evaluate model performance and interpret findings to ensure ethical, equitable, and generalizable AI applications in healthcare.
Collaborate 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:
PhD or equivalent experience in a relevant discipline.
Experience working with healthcare data.
Strong proficiency in machine learning, deep learning, and data science techniques, particularly in healthcare applications.
Expertise in Python, R, SQL, and experience with cloud computing environments (e.g., AWS, Google Cloud Platform, Azure).
Experience with data engineering, model deployment, and MLOps best practices.
Demonstrated ability to translate research into real-world implementations in healthcare settings.
Strong communication skills with the ability to work effectively in a cross-functional, translational research environment.
Experience with federated learning, reinforcement learning, or generative AI in clinical applications.
Proficiency in FHIR, HL7, and healthcare interoperability standards.
Familiarity with NLP and computer vision models for healthcare documentation and imaging applications.
Prior experience in AI model validation, bias mitigation, and explainability in healthcare AI.
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, i ncluding 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.
The ideal candidate will be able to:
Develop and implement machine learning models using structured and unstructured healthcare data from EPIC and other sources.
Design, test, and deploy AI-driven decision support tools within clinical workflows.
Engineer data pipelines for large-scale clinical datasets, ensuring efficiency and security in handling sensitive health information.
Integrate AI solutions with EPIC and cognitive computing platforms to optimize care delivery and reduce clinician burden.
Evaluate model performance and interpret findings to ensure ethical, equitable, and generalizable AI applications in healthcare.
Collaborate 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:
PhD or equivalent experience in a relevant discipline.
Experience working with healthcare data.
Strong proficiency in machine learning, deep learning, and data science techniques, particularly in healthcare applications.
Expertise in Python, R, SQL, and experience with cloud computing environments (e.g., AWS, Google Cloud Platform, Azure).
Experience with data engineering, model deployment, and MLOps best practices.
Demonstrated ability to translate research into real-world implementations in healthcare settings.
Strong communication skills with the ability to work effectively in a cross-functional, translational research environment.
Experience with federated learning, reinforcement learning, or generative AI in clinical applications.
Proficiency in FHIR, HL7, and healthcare interoperability standards.
Familiarity with NLP and computer vision models for healthcare documentation and imaging applications.
Prior 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.
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, i ncluding 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.
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.