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Remote role with broad data science requirements but niche clinical signal specialization creates moderate competition.
Strong healthcare, clinical signals, and regulatory domain requirements limit transferability across industries.
Multiple mandatory niche skills, regulatory/GxP requirements, and principal seniority imply high selection strictness.
Lead integration and analysis of complex biomedical signals, clinical, and real-world healthcare data to generate reproducible insights for clinical studies.
Develop and implement advanced signal processing and machine learning models focused on high-frequency physiological and wearable data for clinical applications.
Build and maintain scalable, high-performance data pipeline systems adhering to best practices and business needs.
PhD, Masters or Bachelor's degree in computer science, biomedical engineering, mathematics, data science or related discipline.
Experience in pharmaceutical or healthcare industry with moderate experience in pharmaceutical and biotech consulting including GxP compliance.
Proficiency in R or Python for machine learning and data analysis, and competence with cloud technologies (e.g., AWS), APIs, relational databases for data integration.
Work Experience Required: Moderate experience in pharmaceutical and biotech consulting as explicitly mentioned.
Experienced in advanced analytical techniques combining signal processing, machine learning, and probabilistic modeling specifically applied to biomedical and clinical data.
Capable of working directly embedded within a pharmaceutical client delivering high-impact technical solutions and maintaining effective stakeholder communication.
Skilled in software engineering best practices, managing complex healthcare data formats including EHR and wearable data, ensuring compliance and interpretability of models.