AD, Statistics (GI) (#2679)

Precision Life Sciences

Job Description

As an Associate Director, GI Statistics, you will be empowered and will have the opportunity to serve as a scientific leader who will provide statistical leadership in the design, analysis, and interpretation of clinical and translational studies at both the compound and therapeutic area levels, promoting innovative designs and methodologies.

How you will contribute:

  • Drives all statistical aspects of development for R&D assets for GI covering design and analysis from early clinical to registrational studies.
  • Drives data-driven decision-making in a multidisciplinary team environment by providing a high level of statistical rigor to the analyses and interpretation of complex data generated.
  • Independently provides strategic and expert statistical input to drug development including feasibility assessments, development plans, complex study designs, and cross-study analyses including statistical methodology, interpretations, regulatory submissions, and follow-up.
  • Establishes and drives the GI program’s functional strategy for resourcing, processes, and standards to maximize efficiency and global data integration.
  • Participates in functional and cross-functional initiatives including process and quality improvements.
  • Serve as global statistical lead for development in GI. Provide statistical leadership and support for internal decision-making, regulatory meetings, submissions, and follow-up.
  • Review key program documents and presentations (portfolio entry document, PRC narratives, strategic plans), attend meetings to develop a comprehensive overview of the existing data, form a deep understanding of the development rationale and strategy and the key questions that need to be answered from data, and help the teams identify any statistical shortfalls and propose solutions to overcome them.
  • Attend scientific conferences and stay abreast with the latest developments with an eye toward acquiring supportive data that can help augment internal data.
  • Play a leadership role in SQS with regard to managing/mentoring junior statisticians and completion of major statistics deliverables and milestones in collaboration with other functions.
  • Stay up-to-date on emerging technologies and associated data analytic techniques, external databases, and novel methodologies that can help derive the maximum value out of data.
  • Drive/participate in the development and implementation of global systems, processes, and standards to maximize quality and efficiency.
  • Leverage standardized analysis methods and reporting standards to maximize global data integrability; identifies best practice for utilization across programs.
  • Provide or identify internal and external statistical expertise and capacity to support development activities. Collaborate/lead in the development of compound/program-level sourcing/vendor strategies and provide oversight of statistical services, ensuring overall quality. Assess, communicate, and propose solutions for internal, external resource, and/or quality issues that may impact deliverables/timelines at the program level. Provide input for planning and management of external budgets related to statistical deliverables.
  • Active participation in external professional initiatives and organizations to identify industry best practices and their applicability.

Minimum Requirements/Qualifications:

  • Associate Director requires Ph.D. in statistics/biostatistics with an emphasis on statistics with at least 5 years of relevant industry experience or MS in statistics with at least 8 years of relevant industry experience.
  • Teamwork is key for this role. the candidate will be expected to routinely interface with other functions in the industry and must have strong interpersonal and people management skills, and the ability to influence others, without direct hierarchical authority, to affect change across organizational boundaries.
  • Expert knowledge across broad areas of statistical methodologies including subgroup analysis, longitudinal data analysis, multivariate methods, predictive modeling, machine learning, and Bayesian modeling. Strong background in statistical modeling in R or SAS with the ability to independently code relevant programs.
  • Advanced knowledge of the pharmaceutical industry, and overall drug development process with expertise in the cross-functional interfaces with the Statistics function.
  • Excellent oral and written communication skills.
  • Strong project management skills.

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