RWE Manager

Position Summary • The Real-World Evidence (RWE) team within client’s Innovative Medicine is seeking a highly motivated Postdoctoral Scientist to join our Data Science & Digital Health (DSDH) Immunology group. • This global role offers a unique opportunity to apply advanced analytics to real-world data (RWD) and contribute to the generation of evidence that informs clinical development, regulatory strategy, and healthcare decision-making across diverse populations and geographies. Key Responsibilities • Conduct high-impact research using large-scale observational databases and clinical trial data to generate real-world insights. • Design and execute studies in collaboration with global cross-functional teams, including clinical, regulatory, epidemiology, and data science. • Develop protocols, statistical analysis plans, and programming specifications aligned with international standards. • Deliver high-quality outputs including analysis-ready datasets, visualizations, and manuscripts for peer-reviewed publication. • Present findings to internal and external stakeholders, including global scientific and regulatory audiences. • Stay current with global trends in RWE methodologies, data privacy regulations, and health technology assessment. Required Qualifications • Masters in Epidemiology, Biostatistics, Data Science, Public Health, Biomedical Informatics, or a related quantitative discipline. Would prefer a PhD with qualifications. • Experience working with real-world data (e.g., electronic health records, claims, registries) from diverse healthcare systems. • Proficiency in R, Python, or SAS; familiarity with OMOP CDM and OHDSI tools is highly desirable. • Strong written and verbal communication skills in English; additional languages are a plus. • Demonstrated ability to work effectively in multicultural, multidisciplinary teams. Preferred Qualifications • Experience working with data sources from low- and middle-income countries (LMICs), including national health surveys, regional registries, or community-based studies. • Familiarity with LMIC health systems, including data infrastructure, care delivery models, and public health priorities. • Knowledge of global health policies, including WHO guidelines, international data governance frameworks, and health equity initiatives. • Experience with digital health technologies, such as mobile health platforms, remote monitoring tools, or AI-enabled diagnostics. • Prior collaboration with pharmaceutical companies, including experience in clinical development, regulatory strategy, or health economics and outcomes research (HEOR). • Experience with international regulatory submissions or health authority interactions. • Familiarity with machine learning, causal inference, and advanced statistical modeling. • Prior publications in peer-reviewed journals and presentations at global conferences.