Senior Data Scientist, Medical Imaging

The role

This person will drive data-centric AI initiatives by understanding how imaging conditions affect deep learning algorithms. They will own analytical pipelines to quantify these effects and work cross-functionally to translate insights into algorithm development and product decisions.

What you will do

• Build robust, reproducible analytical pipelines and visualizations over population-scale data.
• Explore, develop, and validate methods for harmonizing complex data-related factors and image variations.
• Translate findings about data variance and model behaviour into actionable data curation requirements and architectural recommendations.
• Develop annotation protocols for algorithm training and validation for internal product development and FDA submissions.
• Partner with Research Scientists, Machine Learning Engineers, Systems Engineers, Process Engineers, Product and Regulatory teams.
• Derive and present clear analyses from messy data to drive decision-making.

Required qualifications

• Masters or PhD Degree in Data Science, Computer Science, Medical Image Analysis, Statistics, Biomedical Engineering, or a related quantitative field.
• 5+ years (or 3+ with a PhD) of industry experience in Data Science, Machine Learning, or Image Analysis.
• Working command of reproducibility and agreement statistics — variance components, Gage R&R, intraclass correlation, repeatability and reproducibility coefficients, Bland-Altman.
• Deep understanding of medical image data structures and the physical/clinical realities of imaging.
• Familiarity with image processing tools and building algorithms for medical imaging data.
• Expert proficiency in Python and statistical data analysis ecosystems (e.g., pandas, scipy, statsmodels, seaborn/matplotlib).
• Proven ability with large, complex, and messy datasets.
• Hands-on experience developing or fine-tuning deep learning algorithms for computer vision tasks applied to medical images.
• Demonstrated proficiency using modern agentic tools and LLMs (e.g., GitHub Copilot, Gemini, Claude).
• Exceptional ability to distill complex, multi-dimensional data analyses into clear, strategic insights for cross-functional stakeholders.

Nice to have

• Published research specifically related to domain generalization, image harmonization, or out-of-distribution (OOD) detection in medical imaging.
• Experience working with large multi-vendor CT imaging datasets, with an understanding of acquisition and reconstruction protocols.
• Proven track-record in diagnosing data- and annotation-related algorithm performance gaps, and designing data-driven solutions.
• Experience with large-scale data querying and cloud storage (e.g., AWS, SQL).
• Experience developing SaMD products and contributing to regulatory filings.
• Experience with biostats to support FDA submissions.
• Preferably using PyTorch

About the company

Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease using cutting-edge technology. It is a publicly traded company (HTFL) that provides an AI-driven, non-invasive cardiac test.