Manager / Sr. Manager - Global R&D Statistics
Perrigo Company is dedicated to making lives better by bringing high quality and affordable self-care products that consumers trust everywhere they are sold. Help us do it.
This role supports Perrigo R&D as a world class organization in product development speed and reliability.
This is accomplished through managing and improving the new product development statistics program aiming to train, coach and provide team support for multivariate statistical designs, data visualization, and data interpretation.
Responsibilities entail application of statistical methodologies and practical interpretation of analyses including but not limited to:
• Mastery knowledge of descriptive statistics and data visualization with an inherent ability to interpret with an executive summary
• Mastery knowledge of inferential techniques including means testing, regression analysis (univariate and multivariate linear regression), non-linear regression, and logistic regression
• Application of predictive modeling techniques utilized to select the important inputs from observational data including partitioning as well as recursive techniques (bootstrap forest, boosted tree)
• The demonstration of techniques used in determining appropriate sample size to maintain a minimum statistical power
• Design of experiment (DOE): the design of statistically robust, fully randomized experiments used to study materials and process including classical and optimal designs. Utilization of design diagnostics to mitigate random error while balancing resource requirements with the amount of information extracted.
• Familiarity in the utilization of multivariate models with simulation techniques to make robust predictions of the operational results in the population of product that will be produced.
• An ability to convert numerical formulas noted in regulatory guidance’s to coded scripts that allow for efficient application (examples: ASTM 2810, multivariate statistical distance, statistically supported analytical methods)
• Mature technical writing skills used to summarize analysis results into formal statistical analysis reports.
• Leading training events for technical teams that include basic data preparation and data visualization to advanced experimental design applications
• Demonstrated ability to manage analysis projects for product and process development
• Regular use of software used for analysis including JMP, JMP-PRO, PASS with mature techniques for the efficient conversion of data from Microsoft Excel, text files, and through database queries to allow for analysis.
University Degree in related field required - MS or PhD strongly preferred.
Qualified candidates will typically have a minimum of 6 years of applied industrial statistics experience and 2 years supervisory experience.
Preferred candidates will have experience in Research and Development Statistics in the following industries:
Automotive, Consumer Products, Food or Petroleum.
Pharmaceutical experience is not required.