Data Scientist 1

Case Western Reserve University • Cleveland, OH • 2h ago

POSITION OBJECTIVE

Working under general direction, the AI & Data Science Program Lead serves as a technical, operational, and strategic lead within the Cardiovascular Research Institute, with institute-wide responsibility for coordinating, governing, and advancing artificial intelligence (AI), machine learning, and multiomic analytics platforms in support of a precision cardiovascular medicine research program.

This role functions as the central integrator for AI and data science initiatives across multiple laboratories, clinical programs, and institutional partners, with accountability for strategic planning, cross-project coordination, governance frameworks, and translation of advanced analytics into actionable clinical and research insights. This position will lead the development, prioritization, and execution of advanced machine learning initiatives to delineate the health impact of interventions in both experimental and human trials, while establishing standards for reproducibility, validation, and responsible AI use.

The institute is engaged in the integration of large-scale biological datasets to address gaps in knowledge between genomic and environmentally mediated risk. The lab is on the cutting edge of discovery and has interests in the interface of genomic and environmental factors that modulate risk for future heart disease. The laboratory leverages several unique data sets including cutting edge imaging science juxtaposed with environmental variables that monitor the environment to develop next general approaches for personalized medicine. The resources that the lab leverages include the Center for Advanced Heart and Vascular care (CAHVC) is a futuristic academic-corporate partnership with Siemens and Medtronic to develop the next generation of innovative technologies that combine imaging with intervention guided by robotics and artificial intelligence.

ESSENTIAL FUNCTIONS

Lead and oversee the development, validation, and deployment of advanced machine learning and AI approaches to delineate the health impact of interventions in experimental models and human trials. Provide scientific and operational oversight for predictive, prescriptive, and exploratory analytics initiatives across multiple concurrent projects, including risk stratification, response-to-therapy modeling, and outcome prediction. Create, review, and manage predictive models using clinical, imaging, and multiomic datasets. Establish institute-level standards for data collection, preprocessing, quality assurance, reproducibility, model documentation, and version control, ensuring compliance with institutional, regulatory, and ethical requirements.(25%)

Serves as the central point of integration and coordination between clinicians, investigators, data scientists, research administration, IT, and institutional partners. Own responsibility for aligning AI and analytics initiatives with clinical, academic, and operational priorities across the institute, ensuring efficient execution and measurable impact. Manage and coordinate intelligent integration of patient profiles and multimodal datasets to delineate susceptibility to coronary heart disease across multiple studies. Lead cross-disciplinary project planning, define milestones and deliverables, track progress against KPIs, and resolve dependencies or barriers to execution. Utilize data visualization techniques and standardized reporting frameworks to communicate strategic findings, project status, and recommendations to investigators, clinicians, and institutional leadership, supporting decision-making and prioritization. Participate in the planning, optimization, and scaling of analytics platforms and tools across the institute. (25%)

Utilize and advance novel multiomic platforms to predict disease risk in animal models and translational human studies. Provide technical governance and architectural guidance while collaborating with

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