Senior Biostatistician

Overview

• Lead statistical analyses for real-world evidence and clinical research projects, ensuring scientific rigor and impactful outcomes.
• Collaborate with multidisciplinary teams to design studies and analyze complex datasets using advanced methodologies.
• Contribute to protocol development, study design, and endpoint selection for innovative research initiatives.
• Perform rigorous statistical analyses, ensuring data accuracy and compliance with regulatory standards.
• Interpret and present statistical findings to stakeholders, supporting decision-making and strategic planning.
• Provide statistical input for publications, conference presentations, and regulatory deliverables.
• Ensure high-quality documentation and adherence to industry standards throughout statistical processes.
• Stay updated on emerging statistical methodologies and apply them to enhance research outcomes.

Key Responsibilities & Duties

• Lead statistical support for clinical development and real-world evidence initiatives across therapeutic areas.
• Develop and execute statistical analysis plans to address research objectives effectively.
• Perform advanced statistical analyses and provide actionable insights to cross-functional teams.
• Collaborate with clinical, epidemiology, and programming teams to ensure study success.
• Contribute to protocol development, sample size calculations, and hypothesis testing for robust study designs.
• Ensure compliance with regulatory standards and scientific rigor in all statistical outputs.
• Provide statistical insights for publications, regulatory submissions, and payer-facing deliverables.
• Mentor junior statisticians and contribute to team development and knowledge sharing.

Job Requirements

• PhD in Biostatistics, Statistics, Epidemiology, or a related quantitative field.
• Minimum of 5 years of industry experience in biostatistics, preferably in pharma or healthcare analytics.
• Proficiency in statistical programming using R and/or SAS.
• Experience with study design, regression modeling, survival analysis, and causal inference methods.
• Knowledge of claims data, EMR/EHR data, and secondary data sources.
• Familiarity with CDISC standards and clinical trial data structures.
• Strong analytical and problem-solving skills with meticulous attention to detail.
• Excellent communication skills for explaining technical concepts to non-statisticians.