As a Senior Principal Statistical Programmer, you will have the opportunity to work with advanced technical solutions such as R, Shiny, and SAS, allowing you to lead asset teams and mentor junior staff effectively
In this role, you will contribute to global assets across a variety of therapeutic areas, shaping strategic decisions in statistical programming
Your responsibilities will include leading the trial or asset programming team as the Lead Statistical Programmer, ensuring that asset and trial delivery aligns with established timelines and quality standards
You will perform programming activities at both trial and asset levels, including the development of SDTM and ADaM datasets and the creation of specifications
Additionally, you will develop and validate analytical outputs in accordance with the Statistical Analysis Plan and create datasets for integrated analyses like ISS or ISE
You will also be responsible for executing ad-hoc programming activities based on internal and external requests
Actively contributing to statistical programming initiatives, you will support process improvements and innovation while providing expert advice, guidance, and training to trial and asset teams, fostering the development of your colleagues skills
Who are you:BSc or MSc (in a numerate discipline preferably in Mathematics, Statistics or Computer Science)Proven success in a Statistical Programming role within clinical development at a pharmaceutical or biotech company, or at a CRO, equivalent to a minimum of 9 years directly relevant experience
Experience in an international environment is a plus
Advanced skills in R and SAS Full familiarity of CDISC SDTM and ADaM standards (including specifications, Define
xml, and reviewers guide) and underlying concepts
Strong understanding of processes related to clinical development programs, Experience in leading e-submission processes is beneficial
Demonstrated ability to manage assets effectively, ensuring timely delivery and quality outcomesAbility to provide solutions for complex programming challenges and evaluate alternatives to identify optimal solutions