Global Breeding Data Science Co-op
Location:
, Missouri
Posted:
October 19, 2017
Reference:
01KUH
We are seeking an exceptionally talented individual with a passion for innovation for a six month fall co-op in Monsanto's Global Breeding Operations Analytics team. Monsanto's  Analytics team is a cutting edge group providing recommendations and solutions to accelerate and optimize Monsanto's product development.

We foster new game-changing ideas to produce sophisticated, intelligent optimization solutions and predictive models.  As part of our diverse, highly dynamic group, you will be exposed to exciting operations research challenges and will have ample opportunity to work with interdisciplinary scientists (Mathematicians, Predictive Modelers, Machine Learning Experts, Engineers, Operations Managers, and Breeders) to foster your career growth and development while delivering next-generation analytical solutions.

In this role, the successful candidate will use advanced mathematical models, operations research techniques, simulation and strong business acumen to deliver insight, recommendations and solutions for business problems.

You will be required to: 
  •  Formulate and apply mathematical modeling and other optimization methods to develop and interpret information that assists management with decision making, policy formulation or other managerial functions.  

  • Play a crucial role in developing world class logistics and distribution capacity planning and diagnostics, network design, flow path modeling and operations research on regional and global levels.

  • Help drive decisions that optimize total cost, lead time and inventory on strategic and tactical, and more opportunistic levels.

  • Present compelling, validated stories to all levels of organization, including peers, senior management and internal customers to drive both strategic and operational changes in business.

Upon completion of the program, you'll present your findings to an audience of peers and senior management.  End of term presentations are hosted at a designated Monsanto site, where students network with scientists and learn more about future career opportunities at Monsanto.

Dates for this fall co-op are June-December of 2018.
Required:
  • Current enrollment at a university within the U.S., pursuing an M.S. or Ph.D. degree in Operations Research, Industrial Engineering, Mathematics or a related field
  • Must be returning to school upon completion of this internship to continue current or advanced program of study
  • Creative, proactive, bold and out-of-box thinking
  • Theoretical and practical knowledge of operations research and mathematical optimization concepts is a must
  • Expertise in many of the following: Mathematical modeling, simulation, decisions analysis, stochastic models, system dynamics and forecasting
  • Experience and passion for solving analytical problems involving big data sets using quantitative approaches to generate insights from data
  • 1+ years experience with commercial optimization software (i.e., CPLEX, Xpress, Gurobi etc)
  • Strong business aptitude, the ability to rapidly learn new problem domains, and become conversant in the domain with subject matter experts
  • Strong organizational, interpersonal, and proven problem solving abilities
  • Ability to work in a matrix environment, leading & influencing people at varying levels of responsibility.
  • Proven ability to communicate complex qualitative analysis in clear, precise and actionable manner.

Preferred:
  • Experience with object oriented programming (Java/C/C++)
  • Experience with machine learning algorithms and statistical techniques
  • Expertise in probability theory, queuing theory, game theory
  • A good understanding analysis of algorithms and computational complexity
  • Drive for translating business problems into research initiatives that deliver business value
  • Creativity in defining challenging exploratory projects and developing solutions
  • Strong publication record in leading scientific journals
Daily transportation to the Monsanto site is required and will be the responsibility of the student.

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.

Know someone who would be interested in this job? Share it with your network.