Pharmacoepidemiologist

Duration: 9 months/possible extension

Responsibilities:

• The independent analyses of secondary data, including insurance claims, electronic medical record, patient survey, and disease registry.
• Supporting the development of research protocols and statistical analysis plans.
• The recommendation and implementation of appropriate analytical methodology (e.g., propensity score matching, regression analysis etc.) for real world data (RWD) studies.
• The design, development, testing, implementation, validation, documentation, and the maintenance of effective and efficient R programs for reporting observational database studies.In addition, the evaluation of new data sources and the study design for observational studies focusing on safety endpoints.
• You will also be required to represent your function in internal and/or external cross- functional, strategic planning and/or other programs to innovate our use of methodologies or technology.
• The oversight of scientific content of literature reviews, summaries of scientific literature, applying the findings and evidence-based best practices to the design of surveillance and epidemiological investigations, and the development of program recommendations.
• In collaboration with Safety Data Scientists, you will act as a strategic partner for clinical safety scientists to ensure rigorous quantitative approaches are available for molecule safety strategies.

Requirements:

• University degree in Public Health, Epidemiology, Outcomes Research, Health Economics.
• At least 5 years applied working experience with relational real world databases, designing and execution of non-interventional RWD studies.
• A good knowledge of epidemiological study designs and in selecting appropriate pharmacoepidemiologic strategies for molecule plans.
• The ability to analyse data including Clinical Trials, Biomarker and insurance Claims, disease registries, surveys and EHR databases.
• Familiarity with medical terminology and dictionaries (MedDRA, SNOMED, ICD 10, CPT, HCPCS).
• The ability to design, develop, test, document R/Python/SQL programs for observational database studies.
• Be able to transform data and analysis into informative data visualisations, reports and interactive dashboards using (R Shiny, RMarkdown, Python).
• The ability to develop research protocols, statistical analysis plans and recommend analytical methodologies (e.g regression analysis).