Cargill Data Science Operations Research Internship – Spring 2021
As a Data Science Operations Research Intern, from day one, you will be an integral part of the team working with the engineering and data science teams. You will tackle real world challenges, cultivate your curiosity, have client exposure, enjoy both personal and team accomplishments, and have your initiative acknowledged along the way. You will collaborate and build relationships with colleagues and clients who represent diverse work, culture and resolution styles. We look for people who want to grow, support, think and produce. This position is part of the Engineering and Data Sciences team. Your project will connect you back to the business where you will interact with a multidisciplinary team of plant managers, process control engineers etc. You will bring strong technical skills to our data science capabilities. You will explore, connect, and mine data; plus develop models using algorithms for convex optimization and build discrete event simulations. In this position you will be part of the Operations Research Capability where you will be working to solve scheduling, logistics, formulation, assignment, and forecasting problems. 70% – Develop and code optimization and simulation models, completing project deliverables. 30% – Work in a cross-disciplinary project team of engineers, database specialists, data scientists, and business subject-matter experts to develop a project plan and deliverables, plus communicate technical solutions to a non-technical audience. Required Qualifications: Must be currently enrolled in a Masters or PhD program at the University of Illinois, Urbana Champaign in Engineering, Data Science, Computer Science, Statistics, Mathematics, Physics, or related fields with a graduation date of May 2021 or later. Able to complete a semester long part-time internship in Spring 2021 (January – May 2021). Experience developing and testing optimization and simulation models. Strong background in statistics, discrete math, and linear algebra. In-depth knowledge of various classes of optimization problems, e.g., linear, integer, stochastic, network, etc. Interested in learning model deployment in a production setting Proficiency in Python (e.g., pandas, scikit-learn, matplotlib, NumPy) Ability to understand complex and ambiguous business needs and apply the right tools and approaches Curious, self-motivated, driven, and have a passion for problem solving Collaborative team player Excellent communication skills, both written and verbal Strong presentation skills; ability to present technical solutions to non-technical persons in an easy to understand way Preferred Qualifications GPA of 3.0 or above Right to work in the United State without sponsorship Experience in agriculture, commodity, or manufacturing businesses Experience with random number and variate generation Experience using optimization and simulation software e.g., Gurobi and AnyLogic Experience writing queries in SQL and working with database management and analysis tools such as DbVisualizer Click here to apply online
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