Senior AI Scientist, Computational Epidemiology & Genomics

VA Boston Healthcare System; Boston (MA); On-site; USD 130,000 - 180,000; Full time

Job summary

VA Boston Healthcare System is seeking a Sr. Clinical AI Informaticist focused on computational epidemiology to advance translational research and precision medicine.

You will bridge clinical informatics, molecular biology, and AI, integrating EHR data with multi-omics to build predictive models and forecast population health trends. The role leads data pipelines, model development, and methodological publications while collaborating with clinicians, researchers, and software engineers at a

Qualifications

• Must be a U.S. citizen and clears a US government background check.
• Degree: Bachelor’s in computer science or BA/BS with 30 semester hours in math/stat/computer science, with calculus.
• Experience: at least one year of related experience at the GS-11 level or equivalent education substitution per OPM.

Responsibilities

• Apply advanced epidemiological designs and causal inference to train predictive AI/ML models for disease incidence and outcomes.
• Architect data pipelines to harmonize multi-omics with EHR data.
• Develop and validate ML/DL models for high-dimensional data on disease susceptibility and treatment response.
• Perform feature selection and dimensionality reduction to identify biomarkers and clinical variables.
• Audit training data to mitigate bias, confounding, and data drift for equitable AI outputs.
• Lead cross-functional collaboration and contribute to scientific publications and documentation.

Skills

Biostatistics

Epidemiology

ML/AI

Leadership

Communication

Problem solving

Education

Bachelor’s degree in computer science

Math/stat coursework with calculus

Tools

Python

R

SQL

PyTorch

Scikit-learn

Job description

VA Boston Healthcare System is seeking a Sr. Clinical AI Informaticist focused on computational epidemiology to advance translational research and precision medicine.

You will bridge clinical informatics, molecular biology, and AI, integrating EHR data with multi-omics to build predictive models and forecast population health trends. The role leads data pipelines, model development, and methodological publications while collaborating with clinicians, researchers, and software engineers at a