Apply Now: Biostatistician

4 weeks ago


India Capgemini Engineering Full time

Job Description

NOTE- This job requires you to work from Capgemini Office(Pan India).

JOB DESCRIPTION

The Senior Statistician collaborates with Biostatisticians, Statistical Programmers, Clinical Data Managers, Clinical Research Associates, and sponsors teams to provide high-quality, reliable statistical expertise and support.

Additionally. they perform and oversee quality control (QC) of data displays with inferential statistics. Also, Senior Statistician conduct QC analysis datasets prepared by others, maintain project administration files (including protocols, annotated CRFs, statistical analysis plans, annotated shells, programming/QC rules, tracking logs, and project communications),

QUALIFICATIONS FOR ESSENTIAL FUNCTIONS

- Looking for 10+yrs of experience
- Statistical leadership and support to clinical trials.
- Participate in cross-functional study-related activities and team meetings
- Perform sample size calculations when needed
- Author or review statistical analysis plans
- Coordinate with other biostatisticians, statistical programmers and data managers to prepare/conduct/review statistical analyses.
- Ensure the accuracy of final statistical deliverables.
- Provide guidance and supervision to programmers in authoring analysis dataset specifications and programming/validation of tables, listings, and figures.
- Perform validation of analysis variables and statistical outputs
- Participate in other activities and meetings to support Biostatistics and the Development Team as needed.

EDUCATION AND EXPERIENCE REQUIRED

- Master's degree in statistics or related fields with 6+ years of industry experiences as a Statistician
- PhD degree with 3+ years of postgraduate experiences in Biostatistics or equivalent.
- Ability to lead project and manage team members and work collaboratively, effectively, and productively in diverse organization structures.
- Solid statistics background and training, working knowledge of advanced statistical methodologies and SAS programming skills; good understanding of drug development and experiences with clinical trial data analyses/preparation for submissions; good knowledge and understanding of regulatory guidelines



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