Heartflow - Staff Data Scientist
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Requirements
• Education: Masters or PhD Degree in Engineering, Computer Science, Statistics, Data Science or related degree. • Education: • Work Experience: 7+ years (or 5+ with PhD) of proven track record in Data Science, Machine Learning, Computer Vision, or Image Analysis in industry. Have a wealth of experience from working on complex, real-world AI problems in medical imaging or computer vision requiring careful consideration of data needs. • Software: Proficient in Python, including statistical and machine learning packages (e.g. scipy, sklearn, statsmodels, seaborn) with a commitment to writing clean, reproducible and scalable code. Familiarity with image and 3D processing tools like VTK and ITK, and visualization tools like 3DSlicer and MITK, a plus. • Software: • Statistics: Understanding of standard statistical techniques and ability to apply appropriate statistical methods to a range of data structures; experience with medical imaging data a plus. • Statistics: • Data Management: Experience working with data lakes, SQL/No SQL Databases, AWS Cloud Storage, Tableau dashboards. • Data Management: • AI & Medical Imaging: Expertise in deep learning and machine learning models in production. Strong experience working with medical imaging data (CT and vascular imaging) is highly preferred. • AI & Medical Imaging: • (Preferred) Proficiency in Agentic AI Tools: Experience integrating generative AI and agentic tools into daily workflows to act as a force multiplier—accelerating coding, prototyping, and complex data analysis—while demonstrating the critical judgment required to rigorously evaluate AI outputs for accuracy. • (Preferred) Proficiency in Agentic AI Tools: • Communication: Excellent written and verbal communication. Detail orientated but able to describe complex topics in a manner that is digestible to a broad audience. Ability to distill complex analyses into interpretable and actionable findings. • Communication: • Commitment: Committed to the success of the team and successful completion of project - 75% confidence / 100% committed. • Commitment: • Influence without Authority: Able to build trust and obtain cross-functional alignment across departments. • Influence without Authority:
Responsibilities
• Vision & Cross-Functional Leadership: Vision & Cross-Functional Leadership: Engage with cross-functional teams (Product, Research, Engineering, and Process Engineering) and help guide the overarching vision for data analysis, curation, and annotation to improve our AI models. Drive the definition of algorithm and data requirements necessary to deliver on end-point objectives. • Vision & Cross-Functional Leadership: • Data Campaigns and Annotation Strategy: Introduce best practices and efficient processes to enable multiple, large-scale annotation campaigns for continuous AI product improvements. Spearhead the strategic design of data campaigns needed to advance AI algorithms. • Data Campaigns and Annotation Strategy: • Advanced Data Curation & Management: Develop comprehensive data curation strategies for improvements to AI models. Partner with MLOps to architect data management systems for algorithm training and performance validation, and establish data dashboards and monitoring reports. • Advanced Data Curation & Management: • Performance Evaluation and Statistical Analysis: Establish frameworks and develop tools to rigorously evaluate the strengths and weaknesses of model iterations across patient populations. Design and oversee data analyses using statistical techniques to illuminate the performance of our AI algorithms. • Performance Evaluation and Statistical Analysis:
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