Job Description

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 define.pdf, define.xml, 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 IntePros

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