Description
- Under direction from internal statistical leads, provide statistical review, input and interpretation for statistical analysis plans, top line reports, clinical study reports (CSRs), and publications.
- Develop Statistical Analysis Plans (SAPs), Data Presentation Specifications (DPS), Top Line Reports (TLRs) and statistical sections of CSRs.
- Independently develop and apply appropriate statistical methods for ad hoc, post hoc, and Exploratory Data Analyses (EDA), including, but not limited to the following: nonlinear models, propensity score analysis, multiple linear and logistic regression, numerical simulations, bootstrapping, Classification and Regression Tree (CART), meta-analytics, etc.
- Use wide variety of statistical graphics techniques to explore data, derive hypotheses for further study, and better understand and interpret results of clinical trials.
- Contribute to the development of novel statistical methods; eg, modelling for virologic response rates, adherence, resistance markers, etc.
- Author/co-author sections of HA dossiers and summaries for internal working groups.
- Review medical and statistical literature to keep abreast of the latest medical and statistical findings relevant to infectious diseases and vaccines.
- Confirm and further extend upon statistical results produced by external business partners.
- Execute data analyses using appropriate software such as SAS, R, Splus, StatXact, PASS, ADDPLAN, and other software, as needed.
- Responsible for statistical aspects of clinical and pre-clinical research projects including study design, sample size estimation, patient randomization, case report form development, writing statistical analysis plans, statistical analysis and interpretation of data, and reporting of results.
- Work with SAS programmers as part of a biostatistics team.
- Knowledge of applied parametric and nonparametric statistics, strong SAS programming skills, and the ability to translate client needs into statistical practice and the ability to educate clients in the use of statistics are essential.