Data Scientist, Medical Imaging

Role overview Build and evaluate tools that turn medical images into reliable data and models for biomedical research. This hands-on position combines production Python development, traditional image analysis, and AI methods, including work that links imaging with clinical records and reports. The work calls for scientific rigor, reproducibility, and close collaboration across clinical and technical disciplines.

Responsibilities - Develop and maintain Python pipelines that prepare large, varied imaging collections, handling metadata quality and inconsistencies in clinical data. - Apply and assess models for image segmentation, classification, and embeddings, deciding when approaches need adjustment or retraining. - Use methods such as registration, normalization, and feature extraction alongside machine learning where appropriate. - Build and validate models that combine imaging with clinical data or reports. - Connect imaging results with patient records, cohorts, and outcomes using clinical data models and standard vocabularies. - Run scalable workflows with orchestration tools, containers, and cluster or cloud computing; document and test code so others can reproduce results. - Explain findings to clinicians and researchers and contribute to presentations, publications, or open-source tools.

Requirements - A relevant quantitative degree at the master’s or doctoral level, or a bachelor’s degree with equivalent experience. - At least three years of medical image analysis experience in research or industry. - Strong Python skills with scientific computing and deep learning libraries, plus a practice of writing maintainable, tested code. - Familiarity with DICOM, NIfTI, or other medical imaging formats. - Experience applying AI to medical images and using traditional image analysis techniques. - Ability to design rigorous model validation and select appropriate performance measures. - Experience with clinical imaging data and privacy requirements, and comfort working in Linux with version control and containers. - Ability to collaborate across disciplines and explain technical concepts clearly.

Nice to have Experience with workflow orchestration such as Nextflow; clinical data models or vocabularies such as OMOP or FHIR; multimodal models; microscopy or digital pathology; SQL; research publications or open-source work; or federal biomedical research programs.

Benefits and work setup Listed benefits include medical, dental, and vision coverage, paid time off and holidays, retirement matching, education support, referral bonuses, and flexible spending or commuter reimbursement accounts.