Applied AI Health Scientist

Booz Allen Hamilton•Washington, DC

10d•$77,600 - $176,000•Remote

About The Position

This role supports the Advanced Research Projects Agency for Health (ARPA-H), focusing on accelerating better health outcomes through advanced government-funded research and development programs. The Applied AI Health Scientist will contribute expertise across the full lifecycle of AI system development, including data aggregation and curation, model training and benchmarking, and deployment and validation in real-world clinical settings. The position involves working with world-class scientists and engineers, providing strategic assessments of new technologies to senior ARPA-H decision-makers, and producing findings and recommendations on the feasibility and potential impact of future research programs. Responsibilities include managing incoming requirements, facilitating engagements, and shifting focus to fulfill emerging client requests. Attention to detail, flexibility, communication skills, understanding of the client's mission, and problem-solving abilities are crucial for mission success.

Requirements

5+ years of experience with Applied AI in the Health domain
Experience applying advanced ML methods, including LLMs or deep learning, to complex health datasets, including clinical and biomedical data types, such as EHR, genomic, and imaging data
Experience in evaluation methods for AI/ML, including robustness, fairness, interpretability, and reproducibility
Experience in interacting and communicating with senior-level executives, including SES or GS-15
Experience with using Microsoft Office, Excel, Word, and PowerPoint
Ability to review, critique, and guide AI/ML technical work
Ability to operate independently within a fast-paced start-up environment
Master’s degree in a Computer Science, Machine Learning, or Data Science field

Nice To Haves

Experience in healthcare AI or biomedical applications
Experience with the rare disease field
Experience working in technical advisory, evaluation, or SETA-style roles
Experience working with interdisciplinary teams including clinicians and patient stakeholders
Possession of excellent oral and written communication skills
Doctorate degree in Computer Science, Machine Learning, Data Science, or related field

Responsibilities

Review and evaluate AI/ML technical proposals and deliverables from external teams.
Provide guidance on model development, training methods, and validation strategies to identify risks, gaps, or weaknesses and recommend corrective actions.
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, collaborating with clinical SMEs to ensure AI outputs align with clinician expectations and workflows.
Evaluate benchmarking results and provide feedback on methodological soundness.
Advise on deployment considerations, including interpretability, reliability, and safety in real-world settings.
Support program leadership with technical assessments, reports, and recommendations.
Produce high-quality written reports and presentations that synthesize complex technical findings for various audiences.