Sr. Data Scientist, Clinical

<p>Who Are We?</p> <p>Prolaio believes that continuous learning and collaboration can make a significant difference in how heart care is administered. We are creating smarter ways to address heart disease and heart risks by uniting patients, care teams, and researchers on a secure, technology-enabled platform that drives clinical innovation and offers a path towards better patient outcomes.</p> <p>This is precision cardiology, and we know it’s within reach.</p> <p>What Will You Do?</p> <p><strong>The Overview</strong></p> <p>The Senior Data Scientist, Clinical will leverage advanced data science methodologies to advance the science and clinical applications of digital biomarkers. This role involves developing rigorous technical plans and executing complex analyses on multimodal datasets (digital biomarkers from wearable data, electronic health records [EHR], claims) for publication in high-impact medical journals. The successful candidate will build pipelines to prepare analytic datasets from wearable data and EHR and utilize Python and/or R to develop multimodal risk prediction models to describe, predict, and estimate clinical effects.</p> <p><strong>The Specifics</strong></p> <ul> <li><strong>Clinical Analysis &amp; Publication</strong>: Design and execute statistical analyses on large clinical datasets. Author abstracts, statistical analysis plans, conference presentations, and manuscripts for publication in peer-reviewed medical journals.</li> <li><strong>Data Pipeline Development</strong><strong>:</strong>&nbsp; Build, document, and maintain reproducible data pipelines to curate analytic datasets, combining data from multiple assets (e.g., continuous signal data, claims, electronic health records, etc.).</li> <li><strong>Risk Prediction Modeling</strong>: Develop and deploy time-varying and multimodal risk prediction models which extract insights from contextual health data and physiologic signals</li> <li><strong>Scientific Leadership</strong>: Contribute to rigorous science that expands our understanding of digital biomarkers and clinical endpoints in cardiovascular disease in order to enable Prolaio’s ability to support clinical research and cardiovascular care.</li> <li><strong>Cross-Functional Collaboration</strong>: Collaborate cross-functionally with data engineering, operations, clinical, and other teams to ensure data analyses and modeling pipelines align with cross-team standards, scientific validity and company objectives.</li> <li><strong>Advanced Data Abstraction</strong>: Utilize both traditional programmatic and (where applicable) modern LLM-based techniques for complex data processing and clinical abstraction.</li> </ul> <p><strong>Wh