Statistical Programmer

2 weeks ago


India Akkodis Full time
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.

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.

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