Clinical Informatics Scientist - QuantHealth

MD, PhD, PharmD, MSc, MPH, RN, or equivalent degree in clinical informatics, epidemiology, life sciences, biomedical sciences, pharmacy, nursing, public health, or a related clinical or quantitative discipline. 2+ years of hands-on experience working with real-world healthcare data, EHR data, clinical analytics, clinical informatics, or data-driven healthcare research. Practical experience working with clinical datasets and translating clinical concepts into structured analytical definitions. Hands-on experience using Python and SQL for clinical data analysis and data manipulation. Strong understanding of clinical trial design, inclusion/exclusion criteria, endpoints, and longitudinal patient data. Experience developing or validating cohort definitions, phenotypes, progression endpoints, or retrospective clinical features. Familiarity with statistical concepts, observational analyses, and clinical data validation methodologies. Ability to independently investigate clinical questions using both data and scientific literature. Strong analytical thinking, attention to detail, and scientific rigor. Excellent collaboration and communication skills in cross-functional clinical and technical environments.

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.

MD, PhD, PharmD, MSc, MPH, RN, or equivalent degree in clinical informatics, epidemiology, life sciences, biomedical sciences, pharmacy, nursing, public health, or a related clinical or quantitative discipline. 2+ years of hands-on experience working with real-world healthcare data, EHR data, clinical analytics, clinical informatics, or data-driven healthcare research. Practical experience working with clinical datasets and translating clinical concepts into structured analytical definitions. Hands-on experience using Python and SQL for clinical data analysis and data manipulation. Strong understanding of clinical trial design, inclusion/exclusion criteria, endpoints, and longitudinal patient data. Experience developing or validating cohort definitions, phenotypes, progression endpoints, or retrospective clinical features. Familiarity with statistical concepts, observational analyses, and clinical data validation methodologies. Ability to independently investigate clinical questions using both data and scientific literature. Strong analytical thinking, attention to detail, and scientific rigor. Excellent collaboration and communication skills in cross-functional clinical and technical environments.