Monsanto is passionate about using science and technology to improve agriculture. Technology continues to evolve at an ever rapid rate, and it is foremost to Monsanto's success today and in the future to evolve as well. The Global IT Analytics team within Products and Engineering looks to find creative and innovative solutions to enable success within our research pipeline while identifying and capitalizing on new opportunities to maintain and grow our position as the market leader. The ability to examine and optimize our current methods coupled with an eye on the future lends itself to a unique opportunity within our organization.
Monsanto has an opportunity available for a Geospatial Data Scientist to join our Global IT Analytics team within the Products and Engineering organization in IT. The Products and Engineering organization works directly with Monsanto scientists to develop digital products leveraging cutting-edge research and technology platforms revolutionize global agriculture.
You will use the latest mathematical and statistical innovations to propose analytic solutions that accommodate emerging trends in data quantity and quality. You will will design and test algorithms and conduct prototyping to evaluate possible scenarios leveraging computational and statistical techniques for the development of novel approaches for high-throughput big data analyses.
You will also have the opportunity to work collaboratively with interdisciplinary scientists internal and external to Monsanto, organize challenging problems, develop new solutions, and work with business & development teams to ensure these solutions deliver value.
- PhD or PhD completion by May 2017 in Mathematics, Statistics, Spatial Statistics, Geoinformatics, Environmental Modeling, Engineering, Computer Science, or Computational Biology required
- 3+ years of experience with Statistical and Mathematical programming packages (R, Matlab, Python)
- Proficiency in Spatial and/or Temporal Statistical Modeling
- Experience with statistical modeling and data mining
- Experience analyzing and presenting complex data and proven problem solving abilities
- Strong publication record in leading scientific journals
- Strong organizational, interpersonal, and written communication skills
- Ability to work in a matrix environment, leading & influencing people at varying levels of responsibility
- 3+ yrs. experience post PhD building Spatio-Temporal models and predictive models is highly desired
- Expertise in Spatial auto-correlation modeling, Bayesian Statistics, Spatial Econometrics, or Topological data analysis
- Pattern Recognition (Conditional Random Fields, Hidden Markov Models, Maximum Entropy Markov Models, etc)
- Proficiency in Machine learning algorithms and concepts (Ensembles, Deep Learning, SVM, etc.)
- Experience in stochastic modeling and simulation
- Experience working with agricultural/biological scientific data is highly desired
- Drive for translating business problems into research initiatives that deliver business value
- Creativity in defining challenging exploratory projects
- Ability to code in Java, C, Hadoop, MapReduce, PySpark, Spark, C++
A little about us:
At Monsanto, we believe that diverse perspectives solve big challenges and deliver a broad range of solutions to help nourish our growing world.