Operations Research Data Scientist-UIUC Innovation Center

Monsanto Innovation Center - Let’s Reimagine Together

At the Monsanto Innovation Center, we use digital tools and data to drive agricultural innovations which increase efficiency and reduce the amount of water, land, and energy necessary to meet the world’s food, fuel, and fiber needs.

Monsanto is a global modern agriculture company. We develop products and tools to help farmers around the world grow crops while using energy, water, and land more efficiently. We believe innovation has the potential to bring humanity’s needs in balance with the resources of our planet. Monsanto is a Fortune 500 company with over 20,000 employees in 69 countries around the globe.

Employees will help accelerate Monsanto’s growth in emerging technologies and capabilities including engineering, data science, advanced analytics, operations research, phenomics, genomics, plant science and precision breeding technologies. At Monsanto, we believe connecting new talent, ideas and innovations accelerates the discovery needed to feed and sustain our world. Be part of the future of agriculture and identify exciting ways to visualize data to drive actions and decisions that impact product development and farmers globally.

Do you have a passion to:

  • Apply cutting edge advances in mathematical optimization and operations research to solve agriculture challenges?
  • Develop and invent innovative solutions?
  • Create engineering solutions around accessing, visualizing and analyzing peta bytes of data?

Would you like the opportunity to:

  • Solve complex system-level problems in agriculture?
  • Resolve complex issues in innovative, efficient and effective ways?
  • Create ground breaking solutions using data science and operations research?
  • Develop relationships with world class scientists?

Minimum Qualifications:

  • Must be registered as a full-time UIUC student
  • Must be able to commute to the work location daily
  • Cumulative minimum GPA of 3.0/4.0, or equivalent
  • Available up to 20 hours/week during the academic year
  • Available up to 35 - 40 hours/week during the summer semester

The successful candidate will need to demonstrate proficiency in at least two of the following areas: Python, CPLEX, Stochastic optimization methods, network optimization, multi objective optimization, optimizer design for high dimensional convex/non-convex problems, software interfacing to AWS.

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