Associate Director, Non-Clinical Statistics

Lake County, IL, US
Jun 13, 2019
Required Education
Masters Degree/MBA
Position Type
Full time

The Associate Director in Statistics is responsible for providing statistical support across a broad range in nonclinical areas with a focus on Chemistry, Manufacture and Control (CMC), expanding and broadening the application of Biostatistics. He/she is also responsible for helping the group head build the group infrastructure (eg developing SOPs) and mentor junior statisticians or interns.


  • Apply statistical techniques to facilitate better decision-making and improve business operation.
  • Regularly interact with management of different levels in strategy meetings. Contribute to strategic planning to ensure statistically optimized non-clinical development plans and assist in the creation of strategic objectives for regulatory filings.
  • Participate in the planning/design, conduct, analysis, and interpretation of non-clinical studies and regulatory submissions. Participate in establishing departmental and non-clinical SOPs and guidelines. Develop statistical tools to streamline process development, QC testing and troubleshooting.
  • Collaborate with colleagues from other departments to ensure compliance with regulations and help implement regulatory initiatives such as Quality by Design and process validation. Collaborate with external colleagues on consortia and other research projects relevant to biomarker discovery and evaluations.
  • Prepare statistical courses and provide training to scientists. Mentor junior staff, proactively help with both their technical and career development, and seek general feedback and technical input from colleagues.
  • Develop and deliver statistical and scientific publications and present internally and externally.
  • Collaborate with other statisticians in improving and sharing statistical approaches.
  • Maintain and expand expertise in various computing tools to leverage internal and external data sets to drive decisions. Examples of such tools include R, Spotfire, SAS, etc. Continue development of various analysis tools to improve the process.
  • Proactively seek input and review from other experts within and outside the group on various projects and research activities, and share technical information when appropriate. Proactively propose opportunities for productivity improvements and implementation plans.

Level will be based on education & years of experience


  • MS or PhD in Statistics, Biostatistics, or related field with a minimum of 6+ years (PhD) experience or 10+ years (Masters). The level of the position offered will be commensurate with experience.
  • Must have comprehensive knowledge of applied statistical principles & modeling in drug R&D; excellent proficiency in statistical software such as SAS & R; excellent interpersonal and effective verbal and written communication skills; strong programming & computing skills.
  • Jointly with other project team members, develops and evaluates options for meeting project team goals under time and resource constraints.
  • Expertise in statistical methodologies such as predictive modeling and inference, machine learning methods, mixed effects models, multivariate analysis, etc.
  • Builds strong relationships with peers and cross functionally with partners outside of team to enable higher performance. Works collaboratively with function management and multiple stakeholders to develop strategies for addressing issues/requirements that arise in clinical, nonclinical or pharmacology programs, as appropriate. Creates a learning environment, open to suggestions for improvement. Embraces other's ideas, nurtures innovation and manages innovation to reality
  • Broad knowledge of statistical methodology and global regulatory requirements, expertise in drug discovery or development, and an understanding of commercial aspects of drug development. Pharmaceutical or related industry experience with nonclinical studies, as appropriate, including experience and understanding of drug development in the regulated environment preferred.
  • Competent in experimental design, statistical modeling and inferential statistics; actively seeks to acquire knowledge concerning the use of new/novel statistical techniques and their biopharmaceutical applications. Productive in relevant statistical research and problem solving.