Serves as technical lead for advanced analytics, predictive modeling, and machine learning initiatives supporting clinical decision-making and operational optimization.
Designs and validates algorithms for interoperability workflows, clinical informatics systems, and Agile integration reporting.
Ensures compliance with VA data governance, security, and privacy standards.
Present analytical outcomes to managers and stakeholders to guide business model adjustments and future planning.
Translate data into meaningful reports that support healthcare transformation goals.
Collaborate with cross-functional teams to align data strategies with program objectives.
Support predictive modeling and trend analysis to improve veteran healthcare delivery.
Responsible for tasks such as predictive analytics, data migration fidelity, and clinical decision supports.

Master's degree in data science, computer science, health informatics, statistics, or a related quantitative field.
Minimum of 10 years of experience in data analysis or advanced analytics.
Minimum of 5 years applying machine learning and predictive modeling in healthcare or federal health IT environments.
Demonstrated expertise in supporting PI Planning, backlog analysis, velocity metrics and other Agile processes.
Demonstrated experience in interoperability standards (e.g. HL7, FHIR) and clinical terminology (SNOMED, LOINC).
Demonstrated experience in data visualization tools, including PowerBI and Tablueau.
Demonstrated expertise in ETL processes.
Demonstrated expertise in integrating clinical informatics systems (Oracle Health, VISTA, CPRS) and validating data migration fidelity.
Demonstrated experience in programming languages (SQL, Python, R) and frameworks (TensorFlow, PyTorch).
Demonstrated ability to interpret complex datasets and communicate findings to non-technical audiences.

Lead Data Scientist – Healthcare Transformation

Key skills