Statistical Programmer M/F

• An experienced statistical programmer with a strong background in the Life
  Sciences industry.
• Skilled in data analysis , statistical modeling , and programming , with a proven
  track record of contributing to the successful execution of clinical trials and
  research projects.
• Committed to maintaining the highest standards of data quality , regulatory
  compliance , and efficiency in statistical programming.
• Provides statistical programming expertise to deliver high quality
• Develop Analysis Data Model (ADaM) datasets
• Develop (Tables, Figures and Listings (TFL)
  
  
• Output and Programming Specification [ OPS ]
  from the Statistical Analysis Plan [
  SAP ] or a related document
• Program and validate
• standard ADaM
• utility Statistical Analysis Software [ SAS ] macros or R function/package
  following good programming practices

 Statistical Programming: Proficient in SAS, R, and other statistical software.
 Clinical Trials: Extensive experience in clinical trial design, analysis, and reporting.
 Data Management: Data validation, cleaning, and integration.
 Regulatory Compliance: Knowledge of FDA and EMA guidelines.
Programming Languages: SAS, R, Python.
 Statistical Analysis: Data modeling, hypothesis testing, and statistical inference.
 Data Visualization: Generating graphs, charts, and visual representations of data.
 Team Collaboration: Effective communication and teamwork in cross functional
environments.
 Problem Solving: Analyzing complex data challenges and finding innovative
solutions.

Statistical Programming: Proficient in SAS, R, and other statistical software.
 Clinical Trials: Extensive experience in clinical trial design, analysis, and reporting.
 Data Management: Data validation, cleaning, and integration.
 Regulatory Compliance: Knowledge of FDA and EMA guidelines.
Programming Languages: SAS, R, Python.
 Statistical Analysis: Data modeling, hypothesis testing, and statistical inference.
 Data Visualization: Generating graphs, charts, and visual representations of data.
 Team Collaboration: Effective communication and teamwork in cross functional
environments.
 Problem Solving: Analyzing complex data challenges and finding innovative
solutions.