Data Scientist

UVA Health

Virginia (MN)

On-site

USD 89,523 - 143,228

Full time

14 days+

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Job summary

A healthcare organization is seeking a mid-senior level Data Scientist to drive evidence-based decision-making through advanced analytics and machine learning. The ideal candidate will have expertise in causal inference and healthcare data analysis. Responsibilities include designing experiments, developing models, and collaborating with interdisciplinary teams to improve care delivery. The role requires a Master's degree and at least three years of relevant experience, offering an annual compensation range of $89,523.20 - $143,228.80.

Qualifications

PhD or Masters plus three years experience in relevant field.
Demonstrated expertise in design of experiments and observational study design.
Experience working with healthcare data from EHR systems.

Responsibilities

Design and analyze randomized controlled trials and observational research.
Develop machine learning models using healthcare data.
Integrate AI solutions with healthcare systems.

Skills

Causal inference

Experimental design

Healthcare data analysis

Machine learning

Statistical techniques

Education

PhD or Masters in relevant field

Tools

Python

SQL

Job description

Join to apply for the Data Scientist role at UVA Health

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

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.

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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.

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.

Seniority level