Sr. Statistical Programmer
Responsibilities:
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Conduct a comprehensive review of study documents, including Protocol, CRF, and SAP.
Create and assess statistical programs in SAS and/or R to produce CDISC-compliant SDTM and ADAM datasets.
Execution of validation and quality control procedures for programs, datasets, and statistical reports, ensuring alignment with study requirements.
Development and review CDISC SDTM and ADAM mapping specifications.
Produce and review Tables, Figures, and Listings (TFLs) in accordance with the statistical analysis plan.
Review datasets for any pending compliance issues and meticulously document identified issues.
Generation and review of submission documents like define.xml, SDTM annotated CRF, and reviewers guide.
Generation of utility macros and efficient code writing to streamline programming processes.
Communicate effectively within project teams to ensure the timely and budget-compliant completion of assigned tasks.
Adherence to Climb and/or client's Policies and Procedures.
Requirements:
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Master's degree or equivalent, along with relevant formal academic/vocational qualifications and a minimum of 5years of SAS programming experience. Alternatively, a bachelor's degree with at least 5 years of SAS programming experience.
A minimum of 2 years of hands-on CDISC implementation experience. Any experience with R programming will be considered a significant plus.
Proficiency in SAS Programming.
Previous involvement as a production or QC programmer at both product and study levels.
Strong organizational, interpersonal, leadership, and communication skills.
Ability to autonomously manage multiple tasks and projects.
In-depth understanding of FDA regulatory guidance around Study Data and Submission, including familiarity with the Study Data Technical Conformance Guide, FDA Data Submission Standards Catalog, and associated requirements.
A minimum requirement of a strong understanding of CDISC Metadata Submission Guidelines (MSG), Define standards, CDASH, SDTM, ADAM, and controlled terminology standards.
Responsibilities:
β
Conduct a comprehensive review of study documents, including Protocol, CRF, and SAP.
Create and assess statistical programs in SAS and/or R to produce CDISC-compliant SDTM and ADAM datasets.
Execution of validation and quality control procedures for programs, datasets, and statistical reports, ensuring alignment with study requirements.
Development and review CDISC SDTM and ADAM mapping specifications.
Produce and review Tables, Figures, and Listings (TFLs) in accordance with the statistical analysis plan.
Review datasets for any pending compliance issues and meticulously document identified issues.
Generation and review of submission documents like define.xml, SDTM annotated CRF, and reviewers guide.
Generation of utility macros and efficient code writing to streamline programming processes.
Communicate effectively within project teams to ensure the timely and budget-compliant completion of assigned tasks.
Adherence to Climb and/or client's Policies and Procedures.
Requirements:
β
Master's degree or equivalent, along with relevant formal academic/vocational qualifications and a minimum of 5years of SAS programming experience. Alternatively, a bachelor's degree with at least 5 years of SAS programming experience.
A minimum of 2 years of hands-on CDISC implementation experience. Any experience with R programming will be considered a significant plus.
Proficiency in SAS Programming.
Previous involvement as a production or QC programmer at both product and study levels.
Strong organizational, interpersonal, leadership, and communication skills.
Ability to autonomously manage multiple tasks and projects.
In-depth understanding of FDA regulatory guidance around Study Data and Submission, including familiarity with the Study Data Technical Conformance Guide, FDA Data Submission Standards Catalog, and associated requirements.
A minimum requirement of a strong understanding of CDISC Metadata Submission Guidelines (MSG), Define standards, CDASH, SDTM, ADAM, and controlled terminology standards.
