RWE Senior Manager

Job Description

Job Summary:

• The Real-World Evidence (RWE) team within Pharmaceutical Innovative Medicine is seeking a highly motivated Postdoctoral Scientist to join our client.
• 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.

Duties and 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.
• Immunology experience mandatory.
• Experience in Low-Middle income countries.

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.