Healthcare AI Scientist - Work Remotely - Must Have PhD

Job Description: Roles and Responsibilities: • Lead and advise on the design, preparation, and validation of healthcare datasets used across the program, including EHR, genomic, and multimodal data. • Define and assess evaluation strategies and benchmarks that are clinically realistic, methodologically sound, and resistant to shortcut learning or leakage. • Review technical proposals, model submissions, and evaluation results from external teams, providing expert feedback on validity, risks, and interpretability. • Assess data quality, representativeness, and bias, and advise on mitigation strategies appropriate to rare disease contexts. • Evaluate alignment between technical performance metrics and clinical decision-making needs, working closely with clinical SMEs. • Identify gaps between benchmark performance and real-world applicability, and advise on corrective actions. • Serve as a technical bridge between AI developers, clinical experts, and program leadership. • Support the program manager with technical assessments, recommendations, and decision support related to data and evaluation. • Track progress of external partners and identify data- or evaluation-related risks that could impact program outcomes. • Produce high-quality written reports, analyses, and presentations that communicate technical findings to diverse audiences. • This role is suited to candidates who: • Think deeply about measurement, validity, and scientific rigor. • Are comfortable exercising judgment in ambiguous or under-specified evaluation contexts. • Maintain high standards for data quality and methodological integrity. • Communicate clearly across clinical, technical, and programmatic audiences. • Operate with ownership and accountability in high-stakes environments. • Are motivated by advancing AI systems that deliver real clinical and patient impact, not just strong metrics. Requirements: • 5+ years of experience working with healthcare or biomedical data in applied or evaluative roles. • Hands-on experience with EHR, genomic, or multimodal healthcare datasets. • Deep understanding of AI/ML evaluation methods, including benchmarking, robustness, and sources of bias or leakage. • Demonstrated ability to critically review and assess technical work across health data and AI domains. • Strong understanding of data governance, privacy, and compliance in healthcare contexts. • Excellent written and verbal communication skills, with experience producing high-quality technical materials. Preferred Requirements: • Domain expertise in rare disease, diagnostics, or clinical decision support. • Prior experience in technical advisory, evaluation, or SETA-style roles. • Experience collaborating closely with clinicians and healthcare stakeholders. • Experience working in fast-paced, multi-stakeholder, or early-stage environments. Minimum degree: • PhD in Biomedical Informatics, Data Science, Biostatistics, or a related field.