Senior Biostatistician

Overview

• Provide statistical leadership and support for clinical development and real-world evidence initiatives across therapeutic areas.
• Collaborate with cross-functional teams to design and analyze observational studies and evidence generation strategies.
• Perform statistical analyses using validated software such as R or SAS to ensure data accuracy and integrity.
• Contribute to protocol development, study design, and endpoint selection for clinical and observational research.
• Interpret and present statistical results to stakeholders and leadership, ensuring compliance with scientific standards.
• Support the design and analysis of registry studies, claims database studies, and other non-interventional research.
• Provide statistical input for publications, conference abstracts, and regulatory deliverables.
• Ensure high-quality documentation and adherence to regulatory and scientific standards.

Key Responsibilities & Duties

• Lead statistical support for clinical development programs and real-world evidence projects.
• Develop statistical analysis plans, study designs, and endpoint strategies to meet project goals.
• Perform advanced statistical analyses and interpret results for cross-functional teams.
• Collaborate with clinical, epidemiology, and programming teams to ensure study success.
• Contribute to protocol development, sample size calculations, and hypothesis testing.
• Support the design and analysis of registry studies and other observational research.
• Ensure compliance with regulatory standards and scientific rigor in all statistical outputs.
• Provide statistical insights for publications, regulatory submissions, and payer-facing deliverables.

Job Requirements

• PhD in Biostatistics, Statistics, Epidemiology, or 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 attention to detail.
• Excellent communication skills for explaining technical concepts to non-statisticians.