Cardiac CT Image Analyst - Biomedical Imaging / AI Diagnostics About Caristo Diagnostics Caristo Diagnostics is a global leader in AI-powered cardiovascular imaging and biomedical diagnostics. A spinout from the University of Oxford, Caristo's award-winning technology uses artificial intelligence (AI) to transform cardiac CT imaging into a tool for early detection of heart disease. By analyzing routine medical images to identify hidden inflammation and plaque, Caristo enables clinicians to predict heart attack risk before symptoms appear. Our flagship CaRi-Heart® and CaRi-Plaque™ technologies have been featured in The Lancet, JACC, and the European Heart Journal, and Cardiovascular Research CaRi-Plaque™ is now FDA-approved for clinical use in the U.S. Learn more at caristo.com. Position Summary We are seeking a Cardiac CT Image Analyst with a background in biomedical science, medical imaging, radiology, or life sciences to join our expanding Image Analysis team in Stamford, Connecticut. You'll collaborate closely with colleagues in both the U.S. and the U.K., analyzing cardiac CT datasets using Caristo's proprietary AI imaging software. This position is ideal for someone excited by AI-driven healthcare innovation, quantitative image analysis, and the opportunity to shape the future of cardiovascular diagnostics. A comprehensive training program will be provided. Key Responsibilities Analyze cardiac CT images and medical imaging data using Caristo's AI-based software in accordance with company SOPs. Manage and process patient imaging data securely and accurately. Provide timely support to internal and external stakeholders, including physicians and researchers. Identify and flag cases that are non-analyzable due to technical or clinical limitations. Support the development of internal standard operating procedures (SOPs) for image analysis workflows. Participate in risk management activities for new medical device development. Contribute to ongoing research projects (e.g., ground-truth data generation for machine learning). Provide feedback for AI model improvements and software testing.

Required Skills and Experience Essential:

Associate or Bachelor's degree in biomedical science, medical technology, radiology, life sciences, or a related field (e.g., digital health, public health, biomedical engineering). Strong analytical skills and attention to detail. Excellent communication and data interpretation abilities. Proficiency with Microsoft Office, particularly Excel and database management. Strong organizational skills and ability to prioritize multiple tasks. Enthusiasm for medical imaging, AI, and healthcare innovation.

Desirable:

Experience with DICOM images, image segmentation, or quantitative data analysis. Familiarity with Python, MATLAB, or similar data analysis tools. Experience in a clinical, radiology, or biomedical research setting. GCP certification and/or understanding of clinical research standards. Exposure to AI/ML-based imaging platforms or digital diagnostics. Why Join Caristo Be part of a global medical technology company transforming cardiac care through AI and imaging innovation. Join the founding U.S. team and contribute to our FDA-approved product rollout. Work in a collaborative, mission-driven environment that values integrity, innovation, quality, and impact, and which supports personal growth. Share the company values of pushing the boundaries, taking ownership, caring for each other and being candid and professional. Competitive salary and benefits package. Location Stamford, Connecticut (on-site position) Equal Opportunity Caristo Diagnostics is committed to diversity and inclusion. We encourage applications from all qualified individuals, including those seeking to take the next step in their career. Suggested Indeed Skills Tags Biomedical Imaging Cardiac CT AI Imaging Image Analysis Medical Imaging Radiology DICOM Data Analysis Machine Learning Python MATLAB Healthcare Technology Cardiovascular Imaging Quantitative Analysis Medical Device FDA-approved Technology Life Sciences Biomedical Research Clinical Data Digital Health