Lead Statistician
Location: Remote
Experience: 8+ Years
Industry: Clinical Research Organization (CRO) / Pharmaceutical Manufacturing
Position Type: Contract
No H1B
About the Role:We are seeking an experienced Lead Statistician with a strong background in CRO environments and pharmaceutical manufacturing to oversee statistical activities across multiple clinical and non-clinical studies. This is a remote opportunity ideal for someone with extensive experience in statistical planning, regulatory compliance, and cross-functional collaboration within the pharma domain.
Key Responsibilities:Provide statistical leadership across clinical trials and manufacturing studies
Design and review statistical analysis plans (SAPs) and ensure alignment with protocol objectives
Oversee and perform data analysis, interpretation, and presentation of results in regulatory documents, reports, and publications
Ensure compliance with ICH-GCP, FDA, EMA , and other relevant statistical guidelines
Collaborate with cross-functional teams including clinical, data management, regulatory, and QA
Participate in the development and validation of statistical methodologies for complex datasets
Review and validate output including tables, listings, and figures (TLFs)
Provide mentorship and technical guidance to junior statisticians
Represent the statistics function in client meetings and audits
8+ years of experience in statistical analysis within CROs or pharmaceutical manufacturing
Advanced degree in Biostatistics, Statistics, or related field (Master's or Ph.D. preferred)
Strong expertise in SAS or other statistical software (e.g., R, Python)
Excellent understanding of clinical trial design, statistical methodologies, and regulatory frameworks
Prior experience supporting regulatory submissions (NDA/BLA/MAA)
Exceptional communication and client-facing skills
Proven ability to lead statistical projects independently
Experience working in remote/distributed teams
Exposure to CDISC standards (SDTM, ADaM)
Experience with CMC (Chemistry, Manufacturing, and Controls) data in pharma manufacturing studies
Knowledge of statistical aspects of process validation, stability studies , and quality control in pharma
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