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Niche senior ML role in biomedical signal processing reduces applicant density.
Highly domain-specific healthcare and biomedical signal expertise limits cross-industry transferability.
Requires specialized pharma/GxP experience, ML signal-processing expertise, cloud and software engineering practices.
Lead integration and analysis of diverse biomedical and clinical data including electrophysiological, wearable, and electronic health records to generate reproducible insights.
Develop and implement advanced signal processing and machine learning models for clinical applications such as disease phenotyping and predictive modeling.
Design and maintain scalable, high-performance data pipelines ensuring data quality and alignment with business and clinical needs.
PhD, Masters, or Bachelor's degree in computer science, biomedical engineering, mathematics, data science or related field.
Experience within pharmaceutical or healthcare industry.
Proficiency in R or Python with hands-on experience in machine learning, signal processing, and data analysis.
Competence with cloud technologies (e.g., AWS), data extraction via APIs and databases, and software engineering best practices (version control, review, testing).
Experienced in biomedical signal processing and advanced analytical research techniques applied to clinical or healthcare datasets.
Capable of managing end-to-end projects involving large high-frequency longitudinal biomedical data and integrating real-world healthcare datasets.
Skilled in client communication and stakeholder engagement with ability to make timely technical decisions aligned with regulatory compliance and business objectives.