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)