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We are seeking a Senior Data Scientist to support the Department of Veterans Affairs (VA) VHA AI Education Hub, a flagship initiative to advance artificial intelligence literacy and capability across the Veterans Health Administration workforce. In this role, you will lead the design, configuration, and optimization of the AI Education Hub platform, develop an intelligent AI learning assistant and sandbox environment, and ensure seamless integration with VA learning and intranet systems. Your work will directly shape how VA clinicians, administrators, and technical staff learn to leverage AI responsibly within one of the nation's largest federal healthcare ecosystems. The ideal candidate is a self-directed, mission-driven data scientist who thrives at the intersection of advanced machine learning, healthcare data, and large-scale federal technology environments. You bring both deep technical rigor and the communication skills needed to translate complex AI concepts into accessible, policy-aligned educational experiences for a diverse federal workforce.

Lead the end-to-end design, configuration, and continuous optimization of the VHA AI Education Hub platform, ensuring scalable architecture, reliable access, and robust reporting capabilities aligned with VA technical and policy standards. Develop, configure, and maintain the AI learning assistant and sandbox environment embedded within the Education Hub, ensuring all AI capabilities are safe, explainable, and compliant with VA AI governance and ethics policies. Apply supervised, unsupervised, and reinforcement learning techniques to develop and evaluate data models specific to the healthcare domain, including work with synthetic data models and patient cohorts that support workforce training without compromising Veteran data privacy. Architect and manage integrations between the AI Education Hub and VA learning management systems (LMS), intranet platforms, and enterprise data environments, ensuring seamless authentication, content delivery, and learner analytics across VA systems. Design, analyze, and validate healthcare-specific data models within cloud-based analytic environments, applying best practices for data quality, lineage, and governance to support AI/ML model development and educational use cases across VHA. Collaborate with VA stakeholders, contracting officers, and cross-functional technical teams to translate program requirements into actionable data science deliverables, author technical documentation, and present findings and platform performance metrics to government leadership.

Minimum 8 years of professional experience in data science, machine learning, or a closely related quantitative discipline, with demonstrated experience applying ML techniques in complex, data-rich environments. Master's Degree in Statistics, Mathematics, Computer Science, Data Science, or a related field from an accredited institution required. Prior experience supporting federal government agencies or large healthcare organizations, with working knowledge of federal IT policies, data governance frameworks, and health data standards (e.g., HL7, FHIR, or VA-specific data systems). Ability to obtain and maintain a VA Position of Public Trust clearance (Tier 2 / MBI); current clearance or prior VA system access eligibility strongly preferred. Must be authorized to work in the United States; this position does not offer visa sponsorship. Hands-on experience with cloud-based analytic platforms (e.g., AWS GovCloud, Microsoft Azure Government, or equivalent), including deployment of ML models, management of synthetic data environments, and configuration of platform integrations in a secured, policy-governed cloud setting.

1. Experience working directly within VA or VHA programs, including familiarity with VA's Enterprise Data Warehouse (CDW), VA's LMS (TMS), or VA AI/ML governance frameworks such as the VHA AI Strategy or VA Trustworthy AI practices. 2. Demonstrated experience developing or deploying AI-powered learning tools, chatbots, or intelligent tutoring systems within a regulated or federal healthcare environment. 3. Familiarity with synthetic data generation methodologies and privacy-preserving ML techniques (e.g., differential privacy, federated learning) applied to protected health information (PHI) or sensitive federal datasets. 4. Experience authoring Authority to Operate (ATO) documentation, AI risk assessments, or contributing to FedRAMP-authorized platform deployments in support of federal AI initiatives. 5. Publications, presentations, or demonstrated thought leadership in healthcare AI, workforce AI education, or responsible/explainable AI (XAI) within a clinical or public health context.

About Aptive. Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation. We specialize in applying technology, creativity and human-centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day. Founded: 2012. Employees: 300+ nationwide.

Aptive is an equal opportunity employer. We consider all qualified applicants for employment without regard to race, color, national origin, religion, creed, sex, sexual orientation, gender identity, marital status, parental status, veteran status, age, disability, or any other protected class. Veterans, members of the Reserve and National Guard, and transitioning active-duty service members are highly encouraged to apply. About Aptive: Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation. We specialize in applying technology, creativity and human-centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day. Founded: 2012. Employees: 300+ nationwide.