Clinical Transformation Data Scientist, Remote

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.

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), predictive modeling, and advanced analytics to drive clinical transformation initiatives. Education and Experience Master’s in Data Analysis field or a related field required. Doctoral preferred.

Three (3) years of Data Analytics and Database Management experience required Clinical Background preferred Developing and implementing machine learning models and AI-driven solutions to enhance clinical decision-making and operational efficiency. Utilizing predictive modeling and cognitive analytics to extract actionable insights from complex healthcare data. Collaborating with clinical and technical teams to translate data-driven insights into impactful clinical transformation strategies.

Leveraging advanced Epic tools such as Cogito Cloud, Nebula, and Agent Factory to optimize data workflows and analytics processes. Maintaining up-to-date knowledge of emerging data science technologies and best practices in healthcare analytics. Knowledge, Skills and Abilities Proven experience in data science with a focus on machine learning, AI, predictive modeling, and advanced analytics.

Familiarity with AI and cognitive analytics is highly desirable. Experience working with advanced Epic tools (Cogito Cloud, Nebula, Agent Factory) is a strong plus. Epic certifications are highly preferred.

Statistical analysis (experience with tools such as SAS, SPSS) Experience using Tableau and/or Smartsheets software for data visualization Excel expert including macros, visual basic Advanced SQL, Excel and Vizient query languages and database design Metric quantitative and qualitative analysis Experience in data manipulation, transformation, scrubbing and imputation with acute attention to detail Expert at identifying data anomalies Ensures, analyzes and monitors data quality Strong analytic and problem-solving skills Strong writing and editing skills Ability to plan work, set clear direction and coordinate projects in a multi-disciplinary environment Ability to work cooperatively and effectively with people from various organizational levels Remains current with published literature in the fields of medicine, statistical analysis and healthcare operations Change oriented and actively supports process improvement

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