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Job Description

VA Boston Healthcare System is hiring a Senior Data Scientist to build and deploy advanced AI capabilities that support biomedical research and precision medicine. This onsite role in Boston, MA focuses on turning complex, multi-dimensional clinical data into actionable insights using deep learning, representation learning, and production-grade ML systems.

For this position, the salary range is USD 120,548 - 156,715 per year. The work spans exploratory analysis through model development and operationalization, with a strong emphasis on explainability and collaboration with clinical and scientific teams.

Responsibilities

  • Design, implement, and fine-tune state-of-the-art deep learning architectures for multi-omics integration, including models such as Transformers, Graph Neural Networks, and Variational Autoencoders.
  • Build scalable foundation models and generative AI systems for sparse, noisy, and high-dimensional clinical and healthcare datasets.
  • Apply advanced machine learning methods for patient stratification, survival analysis, and disease progression modeling.
  • Develop representation learning and self-supervised learning approaches to embed heterogeneous data streams, including temporal EHR data, continuous clinical monitoring, and structural biological data.
  • Create end-to-end deep learning pipelines that handle missingness, extreme feature dimensionality, and batch-effect correction.
  • Use Explainable AI techniques such as SHAP and Integrated Gradients to deliver biologically interpretable and clinically actionable predictions.
  • Build, scale, and maintain production-grade AI/ML pipelines using distributed GPU computing and cloud environments.
  • Implement best practices including model versioning, automated retraining, validation tracking, and continuous monitoring for data drift.
  • Act as a data science and deep learning subject matter expert, guiding cross-functional teams of clinicians, biologists, and bioinformaticians.
  • Mentor junior data scientists and machine learning engineers on advanced mathematical modeling and neural network architectures.
  • Support scientific and organizational impact by drafting technical documentation, research white papers, and publishing findings in peer-reviewed journals.

Requirements

  • US citizenship and ability to clear a US government background check.
  • A degree in Mathematics, statistics, computer science, data science, or a directly related field, completed at least at the baccalaureate level in an appropriate major field of study.

Skills and Tools

Deep learning frameworks: PyTorch or TensorFlow, plus experience with high-level libraries such as PyTorch Lightning, Hugging Face, or PyG (PyTorch Geometric).

Clinical informatics: experience applying ML/DL to EHR data and working with clinical standards including OMOP and FHIR.

Software engineering: strong Python programming, with capabilities in Git, CI/CD, SQL, and related software engineering practices.

Technologies: Transformers, Graph Neural Networks, Variational Autoencoders, PyTorch, TensorFlow, PyTorch Lightning, Hugging Face, PyG, OMOP, FHIR, Python, Git, CI/CD, SQL, SHAP, Integrated Gradients, distributed GPU computing frameworks, and cloud environments.

Benefits

  • Dental insurance
  • Employee assistance program
  • Flexible spending account
  • Health insurance
  • Health savings account
  • Life insurance
  • Paid time off
  • Retirement plan
  • Vision insurance

How to Apply

Submit a cover letter, resume/CV (must indicate full-time or part-time for each position under work experience and the # of hours), and unofficial transcripts by September 11, 2026, with “Sr. Data Scientist” in the email subject line, to: [email protected].

Reference: For qualification standards, see the OPM website: https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/1500/data-science-series-1560/.

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