Monsanto is seeking a highly motivated individual for our Trait Analytics and Decision Science team under the Biotechnology Trait Testing organization. This position will play a key role in shaping, optimizing, and helping with strategic decisions across emerging technologies. The Statistical Scientist will engage with multi-disciplinary areas across Monsanto Technology providing expertise in experimental planning, analysis, and decision process. They will be responsible for mining and modeling of high-dimensional data, improving process efficiencies, teaching statistical concepts to scientist colleagues, leading special projects in analytics, and collaborating with other analytics teams and Monsanto R&D IT teams for delivery. This position also is expected to identify and implement emerging methodologies that accelerate analytical research objectives in Monsanto’s Biotechnology organization.
Required Education & Skills/Experience:
- Minimum of a PhD in Statistics, Biostatistics, Bioinformatics or a Statistics related discipline -OR- a Master’s Degree in Statistics, Biostatistics, Bioinformatics or a Statistics related discipline with two years of professional experience
- Demonstrated computational skills and experience programming in R and SAS
- Expertise in a wide range of statistical techniques including, but not limited to, experimental design, general and generalized linear mixed models, non-linear mixed models, multivariate statistics, non-parametric analysis, and Bayesian statistics
- Strong problem solving and critical thinking skills
- Experience presenting results to varied audiences and influencing project direction and strategy
- Demonstrated ability to foster and maintain relationships at all levels of the organization
- Ability to actively engage with internal partners and external collaborators to align strategies and success measures in analytics
- Proven statistical consulting and problem solving skills in a research environment
Desired Education & Skills/Experience:
- One or more years of professional experience after PhD
- Background and experience in computational statistics, computational mathematics, machine learning and predictive analytics.
- Background and experience in spatial statistics, geo-referenced data analytics and/or image analytics
- Programming skills in Python
- Knowledge and experience in plant biology, breeding, agronomy, and/or genetics
- Knowledge and experience with agricultural field trials