The Data and Modeling Sciences (D&MS) department is looking for R&D PhD Statisticians for four positions. You will be part of an organization with 30+ statisticians working on a diverse array of interesting problems. You will consult and collaborate closely with researchers, scientists and other statisticians to develop strategies and iterative learning plans using methodologies to integrate multiple types of data and sources. You will discover new methods in partnership with internal and external experts in the field to solve complex problems and advance capabilities. The following are brief details of the four positions:
1. D&MS Statistician with an emphasis in Environmental Safety. Advanced knowledge of nonlinear models is important, background in Bayesian methods is also a plus. A focus on or exposure to safety/risk assessment methods is desired. Mastery in multivariate statistics, linear and mixed-effect models, survival analysis and data mining.
2. D&MS Statistician with an emphasis in Consumer Modeling. Exposure to Marketing Analytics, Economics, and/or Quantitative Behavioral Sciences is a plus. Ph.D. in other quantitative disciplines with expertise in statistics will also be considered. Mastery in multivariate statistics, data mining, psychometric methods and discrete choice. Knowledge of Bayesian methods is a plus.
3. D&MS Statistician with an emphasis in Biological Sciences that include Microbiology, Biotechnology, and/or Clinical. Your skills should show expertise in design of experiments and other methods such as multivariate statistics, linear and non-linear modeling and data mining tools.
4. D&MS Statistician with expertise in the design and analysis of computer experiments, physical experiments and combining the two (hybrid modeling). Collaborate with researchers, engineers and other statisticians on efforts spanning the range of upstream design through manufacturing. Computing skills and expertise in machine learning are a plus.