Principal Biostatistician, FSP
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Job Description
Principal Biostatistician leading clinical-trial design, analysis, and regulatory support for Cytel’s pharmaceutical clients. Applying advanced statistics, R, SAS, and simulation methods across Phase I-IV studies.
Responsibilities:
- Lead Phase I-IV clinical studies across the region
- Provide statistical and development support for client trials
- Contribute expertise to clinical development plans, concept sheets, protocols, and vendor oversight
- Formulate integrated analytical approaches to mine data sources
- Apply statistical methods, machine learning, and deep learning algorithms to discover actionable insights and automate repeatable processes
- Participate in protocol development, study design discussions, and sample size calculations
- Conduct exploratory data analyses to evaluate study trends and support scientific decision-making
- Apply advanced statistical methodologies, including mixed models and complex modeling techniques
- Design and execute simulation studies
- Lead and contribute to efficacy analyses and interpretation of primary and secondary endpoints
- Review CRFs and data review guidelines; develop SAPs, analysis dataset specifications, and TLF specifications
- Perform statistical analyses and interpret results
- Lead study activities and provide strategic statistical guidance to cross-functional teams
- Present statistical methodology, assumptions, and decision implications in clear, non-technical language
- Collaborate with teams to meet project goals and timelines
Requirements:
- Master's degree in Statistics, Biostatistics, or a related discipline
- 8-10 years of biostatistics experience supporting clinical trials within the pharmaceutical or biotechnology industry
- 3-5 years of Study Lead experience working with cross-functional development teams
- Extensive experience in study design, sample size determination, protocol development, SAP development, efficacy analyses, and preparation of clinical study reports, including integrated summaries for regulatory submissions (ISS/ISE)
- Strong knowledge and practical application of advanced statistical methods, including mixed models, longitudinal analyses, and simulation methodologies
- Demonstrated experience performing exploratory statistical analyses
- Strong proficiency in R for statistical analyses, simulations, data visualization, and advanced modeling
- Solid SAS programming skills, including QC of critical outputs, efficacy and safety tables
- Strong knowledge of ICH guidelines and regulatory expectations
- Solid understanding and implementation of CDISC standards for regulatory submissions
- Experience generating ADaM specifications and performing programmatic review of analysis datasets
- Regulatory submission experience (ISS/ISE) strongly desired
- Excellent communication skills with technical and non-technical audiences
- Ability to manage ambiguity, adapt to changing priorities, and deliver high-quality work under tight timelines
Benefits:
- Consistent training, development and support
- Significant professional growth
- Autonomy and ownership while working embedded with a pharmaceutical client
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