Biostatistician at PPD in Morrisville, North Carolina

Biostatistician

Job Description

Company Name:
PPD Development, L.P.
Position Title: Biostatistician

Location: 3900 North Paramount Parkway, Morrisville, NC 27560

Summary of Duties: Acts as a lead statistician with mentorship from senior staff to deliver the project statistician tasks and responsibilities, including analysis database creation, statistical analyses, and creation of statistical tables, listings, and figures. Supports lead statistician on very large, complex studies. Conducts team meetings, maintains project timelines, assesses resources needed, provides resources, and prepares the budget. Ensures that standard operating procedures are being followed and that appropriate project documentation is ongoing. Interacts with the sponsor on all aspects of the project with oversight from a senior team member. Coordinates with programmers and data management personnel as to database maintenance, updating and documentation. Provides guidance for database structures for analysis. Creates or provides specifications for analysis databases. Provides randomization schemes and appropriate documentation. Develops statistical analysis plan, including table and listing specifications, and guide others on the team in its implementation. Programs and validates statistical tables with an emphasis on efficacy endpoints. Provides proper documentation and oversees the work of others who assist in programming and validating. Monitors project budget as it relates to project work scope and communicate proactively with management concerning potential changes in work scope.

Job Qualification

Qualifications

Master's degree in Statistics, Biostatistics, Mathematics, or related field and one (1) year of experience as a Programmer Analyst, Biostatistician, or related role. One (1) year of experience in: Statistical programming (SAS or R); Statistical principles and methodology; Principles of statistical inference, including hypothesis testing and deriving estimates; Parametric models and techniques; Non-parametric modeling techniques; Principles of sample size calculations needed for comparing two samples; and Principles of design of experiments in introducing conditions designed to affect an outcome of interest.