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.