Production Research Data Scientist Co-op – #01SV8

Job Listing No: 9740000

Production Research Data Scientist Co-op – #01SV8

Producemore. Conserve more. Improve lives. That???s Monsanto???s vision for a betterworld. Achieving this vision demands revolutionizing agriculture throughtechnology. Agricultural adoption of GPS, sensors, imaging and state-of-the artprecision equipment has enabled the creation of integrated solutions forfarmers. The ag transformation from simple, mechanical based operations tocomplex computer based systems is possible in part because of data science& analytics. The digital revolution in agriculture rivals past technologychanges such as mechanization, hybrid seeds, and biotechnology. There???s neverbeen a greater demand for your skills in agriculture. So why choose Monsanto? NorthAmerica Production Research Data Scientist Co-ops get hands-on experienceworking side-by-side with data science, field research, and engineering teamsto identify new opportunities and expand existing methods, provide insights,and build practical solutions to complex business problems. Located in St.Louis, Missouri, you will learn the decision-making process in Monsanto???sproduct pipeline and supply, to gain experience of implementing predictiveanalytics model in the Ag industry. Upon completion of the program, you???llpresent your findings to an audience of peers and management.Qualifications:Required:Candidates must be currently enrolled in a Masters or PhD degree
program in Data Science, Statistics, Agricultural Engineering, or a
related quantitative discipline Ability to commit to a 6-month co-op (Jan. – June or June – Dec.)Excellent background in statistics and building predictive modelsDemonstrated programming skills in R, Python, or other scientific
programming languageAbility to communicate complex ideas in a clear,precise and actionable mannerDetail and results-orientated with the ability to work
independentlyAbility to travel within the Midwest (NE, IA, MO, IL, IN, and MI) Desired:General knowledge of agronomy and/or plant breedingProficiency in Spatial and/or Temporal Statistical ModelingExpertise in remote sensing andimagery analysisAbility to solve challenging and complex analytical problems, and
willingness to extend own statistical interests into new fields of
research and development Excellent entrepreneurial thinking, innovation, and real world
problem solving skills 

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