Biostatistician

Position Summary: Provide statistical support in protocol development for observational studies and/or clinical trials. Author and review of statistical analysis plans, analysis dataset specifications, and shells. Work with programming and other cross-functional teams in Phase-4 non-interventional study to develop CRF, validate and review the datasets and results. Conduct programming and analysis for Medical Affairs, RWE studies. Support develops abstract, poster and manuscript as deliverables.

Core Essential Skill sets: Education: PhD or MS in Biostatistics or Statistics Experience in pharmaceutical industry to provide statistical input into the study design, statistical analysis, and reporting of interventional and observational studies Min 4 yrs experience with Phase-4 study, Medical Affairs study, Real World Evience (RWE) or HEOR study. Min 4 yrs experience in statistical software, SAS and R. Min 4 yrs experience with SDTM and ADaM data standards. Min 4 yrs experience with Real World Data (RWD) and RWE methodologies, such as propensity score analysis, causal inference. Min 4 yrs experience with advanced statistical models such as mixed effect model approaches for repeated measures, Machine Learning (ML) methods. Extensive experience providing statistical support for observational studies and clinical trials, including protocol development, analysis, and reporting Practical experience in Phase IV, Medical Affairs, Real-World Evidence (RWE), and Health Technology Assessment (HTA) studies; strong focus on evidence generation and outcomes research Expertise in Real-World Data (RWD) methodologies, including propensity score analysis, causal inference techniques, and other advanced statistical approaches. Highly proficient in R and SAS, with experience developing and maintaining Shiny applications for survival extrapolation, parametric, and spline modeling, supporting both internal tools and client projects. Deep understanding of comparative effectiveness methodologies, including MAIC, STC, ITC, NMA, MTC, IPTW, NMR, and Bucher methods, applied across HTA and RWE submissions Statistical experience on multiple cross-functional projects, ensuring timely delivery of robust and compliant analyses for regulatory and HTA submissions Experience leading statistical strategy and execution for RCTs, observational studies, and RWE programs supporting both regulatory and medical affairs objectives Design/implemented epidemiological and real-world studies integrating registry, claims, and EHR data to inform evidence generation plans and HTA submissions Advanced statistical methodologies including time-to-event and longitudinal modeling (extended Kaplan-Meier, mixed models), propensity score adjustment, and Bayesian network meta-analysis (WinBUGS, SAS Proc MCMC) to support comparative effectiveness and value demonstration. Extensive experience across all clinical trial phases (I–IV) and observational / real-world evidence studies, including randomized controlled trials, epidemiological database analyses, post-marketing safety and effectiveness studies, and health technology assessment submissions Proficiency in SAS and R, with experience developing and reviewing automated R Shiny applications and SAS-based pipelines for health technology assessment and post-authorization safety/effectiveness analyses. History of partnering with Medical Affairs, HEOR, and Clinical Development to interpret and communicate statistical findings for scientific publications, congress presentations, and regulatory interactions (e.g., NICE HTA, Type II variations)