University of Maryland Medical System
Clinical Transformation Data Scientist, Remote
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Job Description
Job Requirements
Join a leading academic medical center dedicated to advancing healthcare through innovation and data-driven insights. We are committed to transforming clinical care by leveraging cutting-edge analytics and fostering a culture of continuous improvement.
We are seeking a highly skilled Clinical Transformation Data Scientist to join our team in 2026. This role focuses on applying advanced data science techniques to healthcare data within an academic medical center setting. The ideal candidate will drive clinical transformation initiatives by developing predictive models, optimizing clinical workflows, and generating actionable insights that improve patient outcomes and operational efficiency.
Responsibilities
- Collaborate with multidisciplinary clinical and research teams to identify opportunities for data-driven clinical transformation.
- Develop, validate, and deploy machine learning models and advanced analytics solutions tailored to healthcare challenges.
- Analyze large, complex healthcare datasets including electronic health records (EHR), imaging, genomics, and patient-reported outcomes.
- Translate data insights into strategic recommendations to enhance clinical decision-making and patient care pathways.
- Support clinical trials and research projects by providing robust data analysis and visualization.
- Ensure compliance with healthcare regulations and data privacy standards in all data handling and analysis activities.
- Communicate findings effectively to both technical and non-technical stakeholders through reports, presentations, and dashboards.
- Stay current with emerging data science methodologies, healthcare technologies, and industry best practices.
Work Experience
The ideal candidate will possess strong technical expertise in the latest data science technologies, applications, and software. This role requires hands-on experience with machine learning, artificial intelligence (AI), predict
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