Clinical Statistical Programmer

General Responsibilities:

  • Collaborate with statisticians and other members of clinical study team to provide statistical programming support for Phase I-III clinical trials;
  • Participate in the review of Statistical Analysis Plans (SAP) and clinical study protocol, Case Report File (CRF), and statistical methodology, statistical programming procedures, analysis file specifications, etc. 
  • Develop and validate complex SAS programs to collect, manage, process and analyze clinical data, create tables, graphs and listings, and generate CDISC SDTM and ADaM datasets, including proper validation, testing and documentation for phase I-III studies. Provide programming specifications for CDISC SDTM and ADaM datasets. 
  • Create and modify standard SAS macros for validation, analysis and generation of clinical reports; provide high quality statistical analyses support for the clinical trial studies using solid statistical theory and SAS/STAT/MACRO/GRAPH /SQL techniques. 
  • Gather and interpret safety and efficacy data that are collected during clinical trials, review data collection and management methodology and assure acceptability and scientific integrity of data collection and analysis through appropriate application of statistical methodology and principles of probability.
  • Use statistical techniques to analyze the clinical trial data and generate Ad-hoc safety summary reports for review by research scientists and medical directors. Also you will be responsible for checking whether the data are out of range of any safety guidelines provided by FDA or other agencies, communicate with project manager and notify client in a timely manner on any abnormal testing results.  
  • Participate in preparing clinical study results for FDA submissions using SAS; writing intense QC documentation for every stage of reporting from extraction to the final reporting of the tables. In addition, assist in client’s inquiries on clinical trial related statistical analysis with developing SAS tools.

Requirements: at least a bachelor’s degree or higher in Statistics, Biostatistics, Mathematics or related field. Master's degree is highly preferred. The candidate must have solid knowledge of statistics, probability, and data analysis, data mining and strong SAS programming skills, etc.