Data Scientist, Medical Imaging (Open Level)

Formation Bio•Boston, NY

20h•$177,500 - $232,000•Hybrid

About The Position

Formation Bio is a technology- and AI-driven pharmaceutical company focused on making drug development and clinical trials more efficient. It builds technology platforms and capabilities to advance drug programs and help bring new medicines to patients. The position leads efforts to integrate advanced imaging analytics and AI into the drug development pipeline. The role applies computer vision and deep learning to medical imaging data, including MRI, X-ray, CT, and PET, to support clinical trials and patient outcomes. It develops models for automated image analysis, disease progression monitoring, and treatment response assessment, and translates imaging data into actionable insights in collaboration with clinical teams, radiologists, and drug development experts. The role is hybrid, with three days per week in the office. Formation Bio is prioritizing candidates in the New York City and Boston metro areas; applicants from the Research Triangle and San Francisco Bay Area may also be considered. Candidates must reside in these locations or be willing to relocate. The posted total compensation range is $177,500–$232,000. Individual compensation depends on role scope, geographic location, skills, and experience. Equity, comprehensive benefits, and generous perks are also offered.

Requirements

PhD in Computer Science, Biomedical Engineering, Medical Physics, or a related field, with a focus on medical imaging.
At least 5 years of post-PhD industry experience developing production-grade AI models for medical imaging applications.
Deep expertise in computer vision and deep learning architectures, including CNNs, U-Net, and Vision Transformers, for medical image analysis.
Proven experience analyzing MRI and X-ray images, including hands-on experience with DICOM standards and medical imaging software.
Strong Python programming skills and expertise with PyTorch or TensorFlow and medical imaging libraries.
Demonstrated ability to collaborate with radiologists and clinical teams to translate medical insights into technical solutions.
Strong communication skills and proven ability to present complex imaging analytics to diverse stakeholders.

Nice To Haves

Experience with regulatory submissions involving imaging endpoints or AI-based image analysis tools.
Experience with multimodal imaging fusion and analysis, including combining MRI, CT, and PET data.
Knowledge of clinical trial design and experience with imaging core lab operations.
Experience with federated learning or privacy-preserving techniques for medical imaging.
Understanding of radiomics and quantitative imaging biomarker development.
Experience with 3D image reconstruction and volumetric analysis.

Responsibilities

Lead development of deep learning models for medical image analysis, focusing on MRI and X-ray for clinical trial applications.
Design and implement automated image processing pipelines for disease detection, segmentation, and quantification across multiple therapeutic areas.
Develop approaches for longitudinal image analysis to track disease progression and treatment efficacy in clinical trials, including AI-based biomarkers and surrogate endpoints.
Collaborate with clinical operations to integrate imaging AI solutions into trial protocols and workflows.
Partner with regulatory teams to ensure imaging biomarkers and AI models meet FDA standards for clinical trial endpoints.
Build scalable infrastructure to process and analyze large-scale medical imaging datasets from multi-site clinical trials.
Present imaging insights and model performance to executive leadership and external partners.