Job Opportunities API

About QuantHealth   QuantHealth is a growing AI startup in the clinical trial space, leveraging AI, biomedical data, knowledge graphs, and real-world patient data to simulate and optimize clinical trials for pharmaceutical companies.    Our platform helps customers simulate clinical trials, reduce development risk and cost, shorten timelines, and improve the probability of clinical trial success.     About the Role   As a Clinical Informatics Scientist in the Clinical Informatics team (R&D), you will play a central role in translating complex clinical and biomedical concepts into robust, computable data representations that power QuantHealth’s clinical simulation platform.   This role sits at the intersection of clinical science, real-world data (RWD), and applied analytics. You will work closely with clinical data scientists, delivery teams, and data engineers to construct clinically valid indication definitions, engineer disease- and treatment-specific features, and develop scalable cohort logic, phenotype libraries, and reusable indication frameworks that power QuantHealth’s simulation and retrospective analysis platform.   The ideal candidate combines strong clinical understanding with hands-on technical and analytical capabilities. You should be comfortable working with large clinical datasets, developing analytical workflows, and writing analytical code, validating clinical assumptions against real-world data, and translating clinical protocols into structured computational logic.   This position is especially well suited for clinically trained professionals with experience working with EHR/RWD datasets and strong interest in data-driven clinical research, clinical informatics, and AI-enabled healthcare systems. The role requires strong clinical judgment and the ability to operate effectively in ambiguous and imperfect real-world data environments.   As the Clinical Informatics organization grows, team members will have opportunities to deepen therapeutic area expertise and evolve into domain-focused scientific leadership roles, including therapeutic area lead and principal-level positions.     Responsibilities   Develop clinically valid indication and cohort definitions using real-world clinical data sources, including EHR, claims, registry, and clinical trial datasets.   Translate clinical trial protocols, eligibility criteria, endpoints, and study designs into computable cohort logic and structured analytical definitions.   Engineer and validate disease-specific and treatment-specific clinical features, surrogate endpoints, and progression markers across multiple therapeutic areas.   Construct and validate longitudinal clinical concepts such as oncology lines of therapy, disease progression endpoints, treatment sequencing, and retrospective outcome measures.   Design and maintain reusable indication frameworks, phenotype definitions, and disease-specific clinical logic that support scalable clinical simulation and retrospective analysis workflows.   Develop standardized clinical feature libraries, progression definitions, and phenotype logic across therapeutic areas.   Develop and maintain analytical workflows and datasets supporting QuantHealth’s simulation and retrospective analysis pipelines.   Query, analyze, and validate large-scale clinical datasets using Python, SQL, and modern analytical tooling.   Collaborate closely with clinical data scientists, delivery teams, and data engineers to ensure clinical cons