Mgr Biostatistics

Summary:

The Biostatistics and Data Management group is looking for a biostatistician to support Exploratory Data Analysis and Wearable Data Analysis within Global Development.  This a position with high visibility for a qualified statistician with experience in the pharmaceutical/biotechnology sector, to collaborate in cross-functional drug development teams to develop and execute innovative statistical analyses to help develop new endpoints (including digital biomarkers), and to perform exploratory data analysis of past trial data to support scientific understanding and clinical strategy. 

Responsibilities:

• Work with a cross-functional team of statisticians, data scientists, engineers, programmers and medical directors to design, execute and analyze studies with novel digital biomarkers, to both establish the reproducibility of digital endpoints and to establish relationships with clinical outcomes.  
• Take initiative on statistical thinking for all aspects of the exploratory analyses, including identification of the scientific questions, development statistical plans, and interpretation and communication of the results.  Identify and apply novel analysis/modeling techniques for interpreting clinical data and enhancing tools for decision making in development programs that span therapeutic areas, from early clinical to completed phase 3 clinical trials.
• Develop and maintain good working relationships with clinical scientists, therapeutic biostatisticians, and external collaborators to drive program strategies and decisions.  Proactively seek inputs from other experts within and outside the group on various projects and research activities and share technical information when appropriate.
• Present at team and management meetings, co-author publications and influence the external pharmaceutical industry and regulatory environment through participation in professional associations, conferences, and publications.
• Maintain and expand expertise in various computing tools to leverage internal and external data sets to drive decisions. Examples of such tools include R, python, SAS, etc.
• Maintain awareness of industry standards and regulatory requirements and communicate within team.  Encourage personal development in the context of project work. Learn and apply techniques to promote teamwork, quality, and motivation

Requirements:

This position requires a PhD or equivalent degree in statistics, biostatistics, biomedical engineering, data sciences, or related disciplines. 

• Solid knowledge of statistical analysis methodologies and computational statistics. The ideal candidate will have an experience in statistical computing, modeling and simulation, linear and nonlinear models, and model-informed drug development
• Expertise in statistical software such as R, python, Matlab, or SAS is required.
• Must be able to work productively in a fast-paced collaborative environment, with demonstrated critical thinking skills, and effective communication and presentation skills.
• Excellent influence and leadership skills, with a track record of collaboration with scientists and physicians.  

Preferred Experience:

Bayesian methodology, data mining or machine learning algorithm. Familiarity with JAGS, R-Shiny, C++ and high-performance scientific computing will be a plus.