Senior Data Scientist, Medical Imaging

About Formation Bio

Formation Bio is a tech and AI driven pharma company differentiated by radically more efficient drug development. 

Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, Formation Bio, founded in 2016 as TrialSpark Inc., has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. Formation Bio partners, acquires, or in-licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients. The company is backed by investors across pharma and tech, including a16z, Sequoia, Sanofi, Thrive Capital, John Doerr, Spark Capital, SV Angel Growth, and others. 

You can read more at the following links:

• Our Vision for AI in Pharma


• Our Current Drug Portfolio


• Our Technology & Platform

At Formation Bio, our values are the driving force behind our mission to revolutionize the pharma industry. Every team and individual at the company shares these same values, and every team and individual plays a key part in our mission to bring new treatments to patients faster and more efficiently.

About the Position

As a Senior 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: $177,500 - $232,000

Compensation Individual compensation is determined by several factors, including role scope, geographic location, and skills & experience. Your offer will reflect where you fall within the range based on these considerations. In addition to base salary, we offer equity, comprehensive benefits, and generous perks. If the posted range doesn't match your expectations, we still encourage you to apply!

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.