Senior Data Scientist

• Design, implement, and fine-tune state-of-the-art deep learning architectures (e.g., Transformers, Graph Neural Networks, Variational Autoencoders) tailored for multi-omics data integration from clinical data modeling
• Build scalable foundation models and generative AI systems capable of processing sparse, noisy, and high-dimensional clinical and healthcare data
• Apply advanced ML frameworks for patient stratification, survival analysis, and disease progression modeling
• Multimodal Data Fusion & Representation Learning
• Develop novel representation learning and self-supervised learning methods to embed heterogeneous data streams (e.g., temporal electronic health records, continuous clinical monitoring, and structural biological data)
• Engineer end-to-end deep learning pipelines that address unique biological data challenges, including missingness, extreme feature dimensions, and batch-effect corrections
• Leverage Explainable AI (XAI) techniques (e.g., SHAP, Integrated Gradients) to ensure deep learning predictions provide biologically interpretable and clinically actionable insights
• AI Engineering & Scalable Infrastructure
• Build, scale, and maintain production-grade AI/ML pipelines utilizing distributed GPU computing frameworks and cloud environments
• Implement best practices, including model versioning, automated retraining, validation tracking, and continuous monitoring of data drift
• Leadership & Scientific Innovation
• Serve as the subject matter expert on data science, artificial intelligence and deep learning, 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
• Represent the organization by drafting technical documentation, research white papers, and publishing findings in top-tier peer-reviewed journals.

• MUST be a US Citizen and MUST clear a US government background check
• Degree: Mathematics, statistics, computer science, data science, or a field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position., * Deep Learning Frameworks: Mastery of PyTorch or TensorFlow, along with experience using high-level libraries like PyTorch Lightning, Hugging Face, or PyG (PyTorch Geometric)
• Clinical Informatics: Practical experience applying ML/DL to EHR data and processing clinical standards (OMOP, FHIR)
• Software Engineering: Expert Python programmer with strong capabilities in Git, CI/CD, SQL, and other software engineering tools
• Deep theoretical understanding of neural network optimization, regularization strategies, and deep generative design
• Exceptional ability to bridge the gap between abstract computer science paradigms and practical, biological hypotheses
• Strong commitment to ethical AI practices, data privacy (HIPAA and Human subjects research regulatory compliance), and mitigating algorithmic bias in healthcare datasets.

Pulled from the full job description

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

The role is based within VA Boston Healthcare System, a leading healthcare system in New England, a major referral center and a hub for clinical and genomics research. The organization is seeking a senior data scientist with an advanced degree in a related field to lead both the exploratory data analysis and the predictive modeling lifecycle for multi-dimensional biomedical data. This role blends rigorous statistical data analytics with advanced machine learning and deep learning (ML/DL) techniques. By integrating, querying, and modeling complex datasets-including national electronic health records (EHR), clinical trial registries, real-world data (RWD), and multi-omics (genomics, methylomics, proteomics, metabolomics) data) to model complex patient phenotypes, uncover actionable patterns, design complex statistical frameworks, and deploy high-performance predictive models to drive precision medicine and clinical discovery.

You will join a multidisciplinary team of clinicians, researchers, data scientists, and software engineers at a nationally recognized healthcare institution. This role offers a unique opportunity to develop and implement advanced data science methods and models for advancing highly impactful translational research.