Principal Data Scientist, Medical Imaging

Principal 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, Sam Altman, John Doerr, Spark Capital, SV Angel Growth, and others.

You can read more at the following links :

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 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

Preferred Qualifications

Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with additional growth in the Research Triangle (NC) and San Francisco Bay Area. Please only apply if you reside in these locations or are willing to relocate.

Compensation :

The target salary range for this role is : $222,000 - $275,000.

Salary ranges are informed by a number of factors including geographic location. The range provided includes base salary only. In addition to base salary, we offer equity, comprehensive benefits, generous perks, hybrid flexibility, and more. If this range doesn't match your expectations, please still apply because we may have something else for you.

You will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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