Applied AI Health Scientist

Booz Allen Hamilton•Usa, DC

9d•Onsite

About The Position

Applied AI Health Scientist The Opportunity: To achieve an organization’s mission, leaders need strong team members who can create processes, communicate requirements, and develop innovative solutions throughout the execution of the mission. Whether completin g an immediate task, recognizing a process gap, recommending a solution, or flexing to support an immerging requirement, our clients need someone who can help manage operations while managing responses to external inquiries in a timely manner . That is why we need you, an experienced Applied AI Scientist for Health who can contribute expertise across the full lifecycle of AI system development: data aggregation and curation, model training and benchmarking, and deployment and validation in real-world clinical settings . As part of our team, you'll support the Advanced Research Projects Agency for Health (ARPA-H), helping conceptualize, create, and execute advanced government-funded research and development programs to accelerate better health outcomes for everyone. Work with world-class scientists and engineers to support the development of high-impact solutions to society's most challenging health problems. Leverage technical expertise to provide strategic assessments of new technologies in support to senior ARPA-H decision makers. Maintain responsibility for producing and presenting findings and recommendations to a team of colleagues and clients on the feasibility and potential impact of future research programs, assisting with the management of current programs, and facilitating commercialization of successfully developed technologies. Y ou'll serv e as a n Applied AI Scientist for Health helping clients to critically assess technical approaches, advise program leadership, and ensure that funded perfo rmers and partners are meeting the highest standards of rigor, reproducibility, and real-world applicability . You will be responsible for managing incoming requirements, facilitating engagements within offices and across the Agency, and is readily available to shift your focus to fulfill emerging client requests. Your attention to detail, flexibility, communication skills, understanding of the client's mission, and problem-solving will enable the mission's 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
A bility 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.