Responsibilities :
- Provide statistical input for protocol development, study design, and CRF development, actively contributing to internal and client meetings, and discussing sample size scenarios.
- Conduct sample size calculations and draft statistical methodology sections for study protocols.
- Oversee the production and quality control of randomization schedules, statistical analysis plans, reports, and other supporting documents.
- Design statistical analysis plans and table shells for study protocols or integrated summaries for NDA submissions.
- Develop SAS programs for generating and quality-checking statistical tables, figures, and listings.
- Perform mapping from raw datasets to CDISC SDTM datasets.
- Produce and quality control , , and annotated case report forms for SDTM submission.
- Develop SAS programs to generate and validate analysis datasets in CDISC ADaM or sponsor-specified formats.
- Review and contribute to the statistical and results sections of clinical study reports and publications.
- Review case report forms and data validation guidelines to ensure data integrity.
- Provide statistical input for Data Monitoring Committee activities and serve as an independent statistician supporting DMC review.
- Understand regulatory requirements and their implications for statistical methodology and analysis.
- Support proposal development and participate in bid defense meetings.
- Review Request for Proposal and Scope of Work documents, ensuring alignment with project goals.
- Manage project budget and forecast resources needed for studies.
- Perform additional responsibilities as assigned by supervisor / manager.
Education :
- Master’s degree in Biostatistics, Mathematics, Statistics, Public Health, or related field required.
- PhD in Biostatistics, Mathematics, Statistics, Public Health, or related field preferred.
Experience :
Minimum of 10 years of experience in statistical analysis of clinical trials data, with a minimum of 3 years within a CRO.
Skills :
- Proficiency in SAS statistical programming.
- Familiarity with general linear models, mixed models, survival analysis, categorical data analysis, and non-parametric methods.
- Knowledge of other statistical and data management software packages is advantageous.
- Strong written and oral communication skills.
- Proficiency in CDISC data standards and models.
- Strong project management and leadership skills.
- Thorough understanding of clinical research regulatory requirements, such as GCP and ICH guidelines.
- Ability to manage multiple tasks and projects effectively.
- Capacity to articulate statistical techniques clearly and interpret results accurately.
LI-DR2
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