Principal Data Scientist, Medical Imaging

About the Position

As a Principal Data Scientist - Medical Imaging at Formation Bio, you will lead our efforts to integrate advanced imaging analytics and AI into our drug development pipeline. In this role, you'll pioneer the application of computer vision and deep learning to medical imaging data (MRI, X-ray, CT, PET) to accelerate clinical trials and improve patient outcomes. You'll develop state-of-the-art models for automated image analysis, disease progression monitoring, and treatment response assessment. Working closely with clinical teams, radiologists, and drug development experts, you'll translate complex imaging data into actionable insights that drive key decisions across our portfolio. This position offers a unique opportunity to revolutionize how medical imaging is leveraged in pharmaceutical development while directly impacting patient care.

Responsibilities

• Lead the development of advanced deep learning models for medical image analysis, focusing on MRI and X-ray modalities for clinical trial applications
• Design and implement automated image processing pipelines for disease detection, segmentation, and quantification across multiple therapeutic areas
• Create innovative approaches for longitudinal image analysis to track disease progression and treatment efficacy in clinical trials, incl. 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 for processing and analyzing large-scale medical imaging datasets from multi-site clinical trials
• Present imaging insights and model performance to executive leadership and external partners

About You

• Required Qualifications
• PhD in Computer Science, Biomedical Engineering, Medical Physics, or related field with focus on medical imaging
• 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 (CNNs, U-Net, Vision Transformers) for medical image analysis
• Proven track record with MRI and X-ray image analysis, including hands-on experience with DICOM standards and medical imaging software
• Strong programming skills in Python with expertise in PyTorch/TensorFlow and medical imaging libraries
• Demonstrated ability to collaborate with radiologists and clinical teams to translate medical insights into technical solutions
• Strong communication skills with proven ability to present complex imaging analytics to diverse stakeholders

• Preferred Qualifications
• Experience with regulatory submissions involving imaging endpoints or AI-based image analysis tools
• Experience with multi-modal imaging fusion and analysis (combining MRI, CT, 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

Total Compensation Range

Total Compensation Range: $204,500 - $267,000

Where We Hire

Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with a hybrid model requiring 3 days per week in office. Applicants from the Research Triangle (NC) and San Francisco Bay Area may also be considered. Please apply only if you reside in these locations or are willing to relocate.

Equal Opportunity

Formation Bio is committed to building a diverse and inclusive team. We are an equal opportunity employer and welcome candidates from all backgrounds. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, national origin, ancestry, sex (including pregnancy, childbirth, breastfeeding, and related medical conditions), gender identity or expression, sexual orientation, age, disability, genetic information, marital status, military or veteran status, or any other characteristic protected by federal, state, or local law.