Health AI Data Scientist — Rare-Disease Diagnostics & Evaluation

General Information Job Code: SHR-DM-05T Location: On Site (Washington, D.C.) Employee Type: Exempt, Full-Time Regular Telework: Ad hoc as determined by client Salary Range: $129,985.76 - $149,483.62 per year (how we pay and promote) Citizenship: U.S. Citizen as required by client Position Overview Are you passionate about turning complex data into actionable insights? As a Health Data Scientist focused on AI & Clinical Data supporting our client, you will play a pivotal role in shaping our success. This is a Science and Engineering and Technical Advisor (SETA) role in the Proactive Health Mission Office at the Advanced Research Projects Agency for Health (ARPA‑H) responsible for providing technical leadership in data design, evaluation strategy, and clinical realism for a multi‑stakeholder program advancing AI diagnostics for rare diseases. Successful candidates will operate at the intersection of health data, AI evaluation, and clinical practice, providing expert guidance to program leadership and external performers. You will ensure that datasets, benchmarks, and evaluation methods are scientifically rigorous, clinically grounded, and aligned with real‑world use so that technical progress translates into meaningful clinical insight and patient impact. Primary Responsibilities While not an exhaustive list, the key duties for the position include: 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. Requirements Minimum Education and Experience: PhD in Biomedical Informatics, Data Science, Biostatistics, or a related field. 7+ years of relevant professional experience with 5+ years of experience working with healthcare or biomedical data in applied or evaluative roles. Basic Requirements: 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. Intermediate experience with Microsoft Office productivity software and collaboration tools such as Microsoft Teams and SharePoint. Skills That Set You Apart: 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. #J-18808-Ljbffr Ripple Effect