Applied AI Scientist (Health) (26-002)
Strategic Analysis, Inc. (SA) Is actively seeking an Applied AI Scientist with deep expertise in artificial intelligence and machine learning to support a program advancing AI diagnostics for rare diseases. This is a Science and Engineering and Technical Advisor (SETA) role, focused on providing technical guidance and oversight.
The Applied Scientist will contribute expertise across the full life-cycle of AI system development: data aggregation and curation, model training and benchmarking, and deployment/validation in real-world clinical settings. The role requires the ability to critically assess technical approaches, advise program leadership, and ensure that funded performers and partners are meeting the highest standards of rigor, reproducibility, and real-world applicability.
Roles and Responsibilities:
• Review and evaluate AI/ML technical proposals and deliverables from external teams.
• Provide guidance on model development, training methods, and validation strategies.
• Advise on integration of multimodal health data (EHR, imaging, genomic, and patient-reported).
• Assess alignment of model architectures and approaches with program goals and clinical use cases.
• Evaluate benchmarking results and provide feedback on methodological soundness.
• Advise on deployment considerations, including interpretability, reliability, and safety in real-world settings.
• Collaborate with clinical SMEs to ensure AI outputs align with clinician expectations and workflows.
• Identify risks, gaps, or weaknesses in technical approaches and recommend corrective actions.
• Support program leadership with technical assessments, reports, and recommendations.
• Produce high-quality written reports and presentations that synthesize complex technical findings for diverse audiences.
This role is suited to candidates who:
• Operate with a high degree of ownership and accountability.
• Exhibit initiative and independence and are effective under conditions of ambiguity.
• Perform with exceptional rigor and precision, maintaining exacting standards of quality.
• Thrive in an environment of high pace and intensity, delivering under demanding deadlines.
• Communicate clearly and professionally across written, verbal, and asynchronous channels.
• Bring ambition and a mission-oriented mindset, motivated by advancing AI systems that achieve real clinical and patient impact.
Minimum Qualifications:
• Advanced degree (Master’s or PhD) in Computer Science, Machine Learning, Data Science, or related field.
• 5+ years of experience in related field
• Experience applying advanced ML methods (LLMs, deep learning, etc) to complex health datasets.
• Familiarity with clinical and biomedical data types, including EHR, genomic, and imaging data.
• Demonstrated ability to review, critique, and guide AI/ML technical work at a high level.
• Strong understanding of evaluation methods for AI/ML, including robustness, fairness, interpretability, and reproducibility.
• Strong written and visual communication skills, with ability to produce high-quality reports and presentations
Preferred Qualifications:
• Experience in healthcare AI or biomedical applications.
• Familiarity with the rare disease field
• Prior involvement in technical advisory, evaluation, or SETA-style roles.
• Experience working with interdisciplinary teams including clinicians and patient stakeholders.
• Experience working in an early-stage, fast-paced, startup environment
Education: Master's degree (PhD preferred) in Computer Science, Machine Learning, Data Science, or related field.
Location: Position is remote.
Travel: Periodic travel may be required
Clearance: Ability to obtain HHS Public Trust.
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The Applied Scientist will contribute expertise across the full life-cycle of AI system development: data aggregation and curation, model training and benchmarking, and deployment/validation in real-world clinical settings. The role requires the ability to critically assess technical approaches, advise program leadership, and ensure that funded performers and partners are meeting the highest standards of rigor, reproducibility, and real-world applicability.
Roles and Responsibilities:
• Review and evaluate AI/ML technical proposals and deliverables from external teams.
• Provide guidance on model development, training methods, and validation strategies.
• Advise on integration of multimodal health data (EHR, imaging, genomic, and patient-reported).
• Assess alignment of model architectures and approaches with program goals and clinical use cases.
• Evaluate benchmarking results and provide feedback on methodological soundness.
• Advise on deployment considerations, including interpretability, reliability, and safety in real-world settings.
• Collaborate with clinical SMEs to ensure AI outputs align with clinician expectations and workflows.
• Identify risks, gaps, or weaknesses in technical approaches and recommend corrective actions.
• Support program leadership with technical assessments, reports, and recommendations.
• Produce high-quality written reports and presentations that synthesize complex technical findings for diverse audiences.
This role is suited to candidates who:
• Operate with a high degree of ownership and accountability.
• Exhibit initiative and independence and are effective under conditions of ambiguity.
• Perform with exceptional rigor and precision, maintaining exacting standards of quality.
• Thrive in an environment of high pace and intensity, delivering under demanding deadlines.
• Communicate clearly and professionally across written, verbal, and asynchronous channels.
• Bring ambition and a mission-oriented mindset, motivated by advancing AI systems that achieve real clinical and patient impact.
Minimum Qualifications:
• Advanced degree (Master’s or PhD) in Computer Science, Machine Learning, Data Science, or related field.
• 5+ years of experience in related field
• Experience applying advanced ML methods (LLMs, deep learning, etc) to complex health datasets.
• Familiarity with clinical and biomedical data types, including EHR, genomic, and imaging data.
• Demonstrated ability to review, critique, and guide AI/ML technical work at a high level.
• Strong understanding of evaluation methods for AI/ML, including robustness, fairness, interpretability, and reproducibility.
• Strong written and visual communication skills, with ability to produce high-quality reports and presentations
Preferred Qualifications:
• Experience in healthcare AI or biomedical applications.
• Familiarity with the rare disease field
• Prior involvement in technical advisory, evaluation, or SETA-style roles.
• Experience working with interdisciplinary teams including clinicians and patient stakeholders.
• Experience working in an early-stage, fast-paced, startup environment
Education: Master's degree (PhD preferred) in Computer Science, Machine Learning, Data Science, or related field.
Location: Position is remote.
Travel: Periodic travel may be required
Clearance: Ability to obtain HHS Public Trust.
Apply tot his job
Apply To this Job