The Associate Director of RWE Analytics plays a crucial role in advancing real-world research on patient health and economic outcomes to support our pipeline products.
Functions:
- Design retrospective and prospective cohort studies in real-world settings to support pipeline and post-marketing products.
- Define patient cohorts and their corresponding health and economic outcomes.
- Program in data process, management, and statistical analysis on registry and large claims/EHR/EMR databases using SAS/SQL/R/Python, etc.
- Determine the selection and application of the most suitable statistical methods for health and economic outcome studies.
- Develop statistical analysis plan and statistical outputs to support internal business strategy and external communications.
- Assist in publications of health and outcome research studies including drafting and reviewing sections of methods and results.
- Assist in development of presentation material to internal and external stakeholders.
- Maintain awareness of new statistical methods, tools and data sources to ensure that projects represent current state of science, and maintains professional knowledge by reading scientific journals, attending internal and external courses, and undertaking methodological research.
Previous Experience:
- A Master’s degree or higher in epidemiology, biostatistics, psychometrics, computer science, or a closely related fields with at least 10 years of hands-on analytical and research experience is required
- Statistical programming is required. Proven strong and advanced programming and analytical abilities in SAS, SQL, R, Python, etc.
- Experience working with large administrative or medical records databases is required
- Experience in statistical modeling of multivariable analysis, repeated measures and specific data distribution to carry out clinical and outcome research is required
- Experience with non-randomized designs is required
- Experience with writing protocols in general and particularly the statistical methods sections of study proposals and/or proposal requests is preferred
- Background in epidemiologic material on etiology, incidence and prevalence of specific diseases, conditions, and therapies (eg. treatment patterns, adherence, effectiveness, etc) is required
- Experience in advanced analytics and data interpretation is preferred