Remote Abdominal/Body Radiologist | Nights | 7 On / 14 Off | Multi-Site Health System | Up to $100K in Bonuses

Join a growing partnership between Imagen Technologies and a leading multi-site healthcare system serving one of the largest patient populations on Long Island, NY. This role combines the scale of an established health system with Imagen’s physician-led model, advanced technology, and fully supported remote infrastructure. We’re seeking a fellowship-trained Abdominal/Body Radiologist for an overnight 7 on / 14 off schedule, interpreting a consistent, high-quality worklist of body imaging studies, including CT and MRI of the chest, abdomen, and pelvis, with exposure to a range of complex and high-acuity cases. This structure offers a strong subspecialty focus with extended time off between shifts. Imagen’s AI-enabled platform and 24/7 support teams are designed to streamline workflow, reduce administrative burden, and allow you to focus on clinical care. This is an opportunity to practice high-impact body imaging remotely in a dedicated overnight setting, with a predictable schedule and significant time off built in. About the Position: Full-time, remote position supporting a large, multi-site health system 7 on / 14 off - 11pm - 7am EST Competitive salary, benefits package, and malpractice insurance Base salary + productivity bonuses with uncapped earning potential Up to $100,000 in signing and retention bonuses Duties and Responsibilities: Interpret a high volume of abdominal and body imaging studies, including CT and MRI of the chest, abdomen, and pelvis Provide accurate, timely, and clinically actionable reports to support patient care across a large health system Collaborate with multidisciplinary teams including oncology, surgery, and internal medicine Utilize AI-enabled tools and advanced workflow technology to enhance productivity and diagnostic accuracy Participate in quality assurance and peer review initiatives to support continuous clinical improvement Qualifications: ABR or AOBR Board Certified or Board Eligible Fellowship training in Abdominal/Body Imaging Demonstrated experience interpreting body CT and MRI, including complex cross-sectional imaging About Imagen: Imagen's mission is to ensure every patient receives the right diagnosis at the right time. We are a leading provider of technology-enabled diagnostic imaging services focused on improving diagnostic imaging quality, cost, and accessibility. Our Medical Practice is made up of 100+ specialists including diagnostic and interventional radiologists, cardiologists, and optometrists. Our FDA-cleared software analyzes the content of medical images and produces diagnoses, improving clinicians’ diagnostic accuracy by highlighting detected pathology. To learn more about how Imagen is making high-quality healthcare accessible to everyone, visit our website: https://imagen.ai/solutions/ The base salary for this role is $475,000. Please note that the salary is a guideline, and individual total compensation will vary based on factors such as productivity, qualifications, skill level, competencies, and work location. Imagen Technologies maintains a Substance Abuse and Testing policy. Being under the influence of alcohol or controlled substances while on the job or while conducting business on Imagen’s behalf is prohibited. Any offer of employment will be made contingent upon successful completion of a drug test, subject to compliance with all applicable federal, state, and local laws. Imagen is committed to the principle of equal employment opportunity for all employees and applicants for employment and prohibits discrimination and harassment of any kind without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Imagen will not tolerate discrimination or harassment based on any of these characteristics. This policy applies to all terms and conditions of emplo ... (truncated, view full listing at source)