RESPONSIBILITIES

• Provides statistical leadership for clinical development programs in Phases 1-2.
• Statistical collaboration in clinical design, biomarker and clinical pharmacology strategy, methodology, data analysis and interpretation, reporting.
• Continually develops statistical skills and use or invent novel statistical methodology when appropriate.
• Develops & advises other team members. Specifically, serves as an Early Development Global Biometric Sciences (EDGBS) Biostatistics Lead.
• Along with the leads from Exploratory Clinical and Translational Research (ECTR), regulatory, and other R&D functions, the EDGBS Lead is responsible for providing scientific and strategic leadership and has a shared responsibility for developing the clinical/regulatory strategy and translational research and development approaches until transition to Full Development.
• Provides strategic input into the design/planning of clinical development plans, clinical trial designs, data analysis approaches, interpretation of findings and crafting of key messages, and represents GBS at regulatory meetings when appropriate.
• Accountable for the performance and deliverables of the GBS team and develops an effective partnership with the GBS Planning and Execution Lead to ensure the team's ability to execute with quality in agreed to timelines.
• Plays a key role in the continuous improvement of EDGBS, which includes but is not limited to improving processes and contributing to the strategic initiatives/directions of GBS.

REQUIREMENTS

• PhD in biostatistics, statistical genetics, or scientific field w/ strong statistical theory and methods, or equivalent.
• Minimum 4 years experience with clinical trials.
• Strong communication skills, both written and oral, collaboration, and leadership skills.
• Demonstrated skills in analysis of pharmacokinetic, pharmacodynamic, safety, efficacy & biomarker data, with an understanding of Bayesian statistics, multiplicity issues, and high-throughput genetic & genomic data.
• External presence as evidenced by publications and/or presentations.
• Experienced in a variety of (Bayesian) model-based adaptive designs from Phase 1 to Phase 2b preferred.
• Expertise in SAS required, S-plus or R preferred, including advanced statistical analysis, data manipulation, graphing and good software design.
• Good understanding of regulatory requirements and clinical trial design.
• Knowledge and ability to learn biomarker biology and incorporate biology into analysis & interpretation.
• Ability to work as part of a highly skilled team.
• Demonstrated ability to influence matrix teams .
• Less experienced but strong candidates meeting most but not all of the requirements may be considered at a less senior level.

LOCALE

HOW TO APPLY