Data Scientist Jobs

About The Position

Requirements

• Demonstrated experience designing and evaluating AI/ML solutions in production or enterprise environments, with a strong portfolio of applied machine learning work across the full model development lifecycle.
• Equivalent combination of technical training, certifications, and hands-on experience in data science or machine learning will be considered.
• Ability to obtain and maintain VA network access and a Position of Public Trust designation as required; must be able to satisfy VA background investigation requirements prior to onboarding.
• Must be authorized to work in the United States; this position does not offer visa sponsorship.
• Proficiency with AI/ML frameworks and tools (e.g., Python, scikit-learn, TensorFlow, PyTorch) and experience working with structured and unstructured healthcare datasets, including EHR data or claims data.

Nice To Haves

• Prior experience supporting federal agency clients or healthcare organizations is preferred; familiarity with VA systems, federal AI policy (e.g., EO 13960, OMB AI guidance), or HHS/CMS data environments is a plus.
• Experience with AI/ML governance, responsible AI frameworks, or model risk management in a regulated industry such as federal healthcare or finance.
• Familiarity with VA or federal health data standards, including HL7 FHIR, ICD-10 coding, or Veterans health records systems.
• Knowledge of federal AI policy and compliance requirements, including NIST AI Risk Management Framework (AI RMF) or related standards.
• Experience communicating AI/ML findings and recommendations to non-technical senior leadership or federal program offices.
• Background in NLP, computer vision, or predictive analytics applied to clinical workflows, population health, or healthcare operations.

Responsibilities

• Design and evaluate AI/ML solution approaches tailored to VA healthcare operations, assessing technical feasibility, performance, and alignment with mission objectives.
• Conduct rigorous assessments of existing and proposed AI/ML models, including evaluation of accuracy, bias, fairness, and explainability in clinical and operational contexts.
• Support the development and implementation of AI governance frameworks, policies, and best practices consistent with federal AI regulations and VA-specific guidance.
• Collaborate with VA stakeholders, program managers, and subject matter experts to translate operational healthcare challenges into well-scoped AI/ML problem statements and solution roadmaps.
• Document technical findings, model evaluation results, and strategic recommendations in clear written deliverables suitable for both technical and executive audiences.
• Monitor emerging AI/ML trends, tools, and federal policy developments to provide informed recommendations that keep VA's AI strategy current, compliant, and competitive.