Oncology Informatics Specialist (Physician Reviewer)

Every cancer patient deserves access to treatment options. Massive Bio is an AI-powered precision medicine platform transforming how cancer patients discover and access clinical trials by eliminating the barriers of geography, financial constraints, and information asymmetry that have historically limited enrollment.

Founded in 2015 and headquartered in US, Massive Bio is scaling its impact globally by powering operations across multiple countries and bringing innovative cancer treatment options to a rapidly growing and diverse population of patients. Through our proprietary AI platform, we connect individuals to clinical trials worldwide and partner with leading pharmaceutical companies, contract research organizations (CROs), and healthcare systems to accelerate drug development and expand equitable access to cutting-edge therapies.

The Oncology Informatics Specialist sits at the intersection of clinical medicine, clinical research, and AI-powered healthcare technology. In this role, you will provide clinical review and quality assurance for an AI-driven platform that helps identify potential matches between cancer patients and relevant clinical trials.

You will review AI-generated clinical data against source medical records, assess patient eligibility based on clinical trial inclusion and exclusion criteria, and apply clinical judgment to identify details that may affect trial eligibility. You will also work closely with Clinical Operations, Product, and Engineering teams to support the quality, consistency, and continuous improvement of AI-driven patient-to-trial matching workflows.

This role is well suited to physicians interested in gaining experience across clinical trials, clinical data, healthcare technology, and AI, with exposure to pharma-sponsored research and clinical operations.

• Review and validate AI-abstracted clinical data, including diagnosis, disease stage, biomarkers, treatment history, laboratory results, and imaging findings, against source medical records for accuracy and completeness.

• Evaluate patient eligibility against clinical trial inclusion and exclusion criteria as a core part of the patient to trial matching process.

• Serve as a clinical quality assurance checkpoint within the human in theloop (HITL) review process, identifying abstraction errors, edge cases, and potential misinterpretations of clinical trial criteria.

• Apply clinical knowledge in oncology and hematology to identify relevant clinical details that may affect patient eligibility, including prior treatment history, treatment sequencing, biomarker requirements, comorbidities, and staging considerations.

• Collaborate with the Clinical Operations team on referral-to-enrollment workflows to help ensure that matched patients meet the relevant clinical criteria for the trials to which they are referred.

• Document clinical and QA findings clearly and consistently for both clinical and non-clinical stakeholders.

• Work with Product and Engineering teams to communicate recurring data or interpretation issues and contribute to improvements in AI-driven clinical matching workflows.

• Support quality, consistency, and scalability as patient review volume grows.

• MD or equivalent medical degree.

• Physicians early in their careers are encouraged to apply.

• Working knowledge of and genuine interest in oncology and/or hematology.

• Ability to review and interpret real-world medical records, including EHR data, pathology reports, imaging reports, laboratory results, and treatment histories.

• Strong clinical reasoning and attention to detail, particularly when interpreting complex or incomplete clinical information.

• Strong written communication skills, with the ability to clearly document clinical reasoning and communicate findings to both clinical and non clinical stakeholders.

• Interest in the application of AI and machine learning in healthcare.

• Ability to work effectively at the intersection of clinical judgment, data, and technology.

• Previous exposure to pharma-sponsored clinical trials.

• Experience evaluating clinical trial inclusion and exclusion criteria.

• Experience supporting clinical trial recruitment or patient screening.

• Familiarity with clinical data management or clinical research workflows.

• Interest in Clinical Operations, Medical Affairs, Clinical Data Management, or related areas.