
Senior Data Analyst and Statistical Programming Lead
4 hours ago
Job Overview:
We are seeking a skilled Statistical Programmer to lead statistical programming support for multiple clinical projects using SAS. This role involves providing expert consultation across the organization and delivering key regulatory-compliant output.
Main Responsibilities:
- To provide lead statistical programming support for multiple clinical research study projects or study teams, ensuring sound methodologies are adopted and proficiency of programming techniques required for clinical trials research involving CDISC standards is established.
- To develop statistical programming with SAS (Base and Macros) and provide expert consultation to projects across the company including statistical programming methodology.
- To deliver key output based on established proficiency of regulatory requirements for clinical research E-submissions and/or study requirements for Sponsor, Regulatory, Investigator or Safety review meetings.
- To develop detailed programming documentation and annotations including specifications, review of mock shells, adhering to relevant Standard Operating Procedures and contributing to standardization efforts.
- To write well-documented, efficient, and high-quality code, conduct code review, support cross-functional programming activities, and programming validation as needed.
- To remain current with current statistical programming techniques to ensure adoption of sound methodologies.
- To present statistical programming topics internally and present at external conferences.
Requirements:
- Bachelor's degree plus 4 years of Statistical programming experience as a CDISC/TLF Statistical programmer in Pharmaceutical/CRO environment; education in a scientific discipline preferred.
- Understanding of GCP principles and other regulatory standards (e.g., FDA, EMA, and ICH guidance and recommendations) in Clinical Research.
- Strong analytical skills with ability to process scientific and medical data.
- Proficient in statistical programming skills in SAS; familiarity with R, Python or other relevant statistical software beneficial.
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