Statistical Programmer M/F @ Akkodis

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: G enerating 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.

Life sciences

• 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.