Want to build a stronger, more sustainable future and cultivate your career? Join Cargill’s global team of 160,000 employees who use new technologies, dynamic insights and over 154 years of experience to connect farmers with markets, customers with ingredients, and people and animals with the food they need to thrive. Internship Summary: YOU MUST CURRENTLY BE ENROLLED AT THE UNIVERSITY OF ILLINOIS, URBANA-CHAMPAIGN (UIUC) FOR THIS INTERNSHIP OPPORTUNITY WITH CARGILL AT THE UIUC RESEARCH PARK Want to work at the forefront of artificial intelligence and agriculture? In partnership with Cargill, at the University of Illinois, Urbana Champaign (UIUC) research park, you will be given the opportunity as a graduate level intern to apply knowledge gained in the classroom to a real-life environment and then multiply by tenfold. Cargill has a significant presence across agricultural supply chains and animal nutrition & health. With that footprint comes massive amounts of data, both structured and unstructured, that can drive decision-making. You will be developing projects with advanced machine learning techniques that also use external inputs with continuously flowing data. By employing more sophisticated methods than standard data analysis, your solutions will deliver significant value to Cargill’s business. As a Data Science Intern, from day one, you will be an integral part of the team. You will tackle real challenges, cultivate your curiosity, be visible, and build relationships with colleagues and clients who represent diverse work, culture, and styles of communication. Your initiative and insight will be acknowledged and valued, and you’ll be able to celebrate your own accomplishments as well as those of your team. We look for people who want to grow, support, think and produce. Key Accountabilities: Your project will connect you to key decision-makers, and you will interact with a multidisciplinary team. You’ll bring your strong technical skills to the table and enrich our data science practice. You will explore, connect, and mine data for its predictive value, and you’ll use advanced machine learning techniques to design and build predictive models. This position is part of the Engineering and Data Sciences team. Specifically, you will be part of the Molecular Modeling and Data Science (MMDS) capability where you will be working to solve challenges with firsthand microbiome data, develop prototypes and research on new methods for analyzing the data. 50% – Develop and code machine learning models by applying algorithms to large data sets 20% – Run exploratory data analysis to visualize data sets and present on the findings 20% – Work in a cross-disciplinary project team of software 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. 10% – Design strategies and propose algorithms to analyze and leverage data from a variety of sources. Job Location: This position is located at the University of Illinois, Urbana-Champaign in Champaign, IL. Required Qualifications: Must be currently enrolled in a Master’s or PhD program at the University of Illinois, Urbana Champaign in Data Science, Machine Learning, Computer Science, Computational Linguistics, Statistics, Mathematics, Engineering, Physics, or related fields with a graduation date of December 2023 or later Must be able to complete, at a minimum, a semester long internship in Summer 2023 (June – August) Demonstrated abilities with applied programming in Python (e.g. numpy, pandas, scikit-learn, bokeh, nltk, tensorflow, keras) or R (e.g. ggplot2, cluster, dplyr, caret) Knowledge of several supervised learning algorithms (such as: linear regression, decision trees, neural networks, ensemble methods) Strong verbal and written communication skills Interest in learning a machine learning model development and deployment life cycle Curious, self-motivated, driven, and have a passion for problem solving Collaborative team player Preferred Qualifications: Hands-on experience analyzing large data sets Experience contributing to projects centered around supervised machine learning or statistical inference, both in development and testing Experience working in a cloud environment e.g., Amazon Web Services Experience with Big Data development in Hadoop and Spark frameworks 3.0 GPA or above is preferred Entering final year of graduate program Equal Opportunity Employer, including Disability/Vet.
