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Data Science Computer Vision Intern 2020/2021 at UIUC Research Park

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Job ID UNI05875 Date posted 03/02/2020 Location : Champaign, Illinois |

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. With that footprint comes massive amounts of data, much of it in the form of pictures or video. Computer vision is a key and growing aspect of the Cargill Data Science team. Detecting objects, estimating size, categorizing variations, and tracking objects are all important inputs to the agricultural supply chain and building out a platform utilizing these capabilities is an exciting challenge.

As a Data Science 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 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. You will bring strong technical skills to our data science capabilities and connect back to the business where you will interact with a multidisciplinary team. In this position you will be part of the Computer Vision Capability where you will be working to solve a variety of technical challenges from developing models, IoT prototypes, exploring and mining data and deploying the solution to production.

70% - Develop and code models by applying algorithms to large structured as well as unstructured data, completing project deliverables.
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: University of Illinois, Urbana-Champaign in Champaign, IL.

Required Qualifications:
• Must be currently enrolled in a Masters 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 May 2021 or later.
• Able to complete a minimum semester long internship either Fall 2020 or Spring 2021.
• Experience developing and testing machine learning or statistical projects.
• Strong background in Computer Vision including Image/Video Processing, Object Detection, Classification and Tracking. Knowledge and experience on using deep learning tools (e.g. TensorFlow, MXNet, PyTorch, etc.) for image/video analytics.
• In-depth knowledge of various other modeling algorithms, e.g., regression, trees-based models, neural networks, ensembles, etc.
• Interested in learning model deployment in a production setting.
• Proficiency in Python (e.g., pandas, scikit-learn, bokeh, 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 3.0 or above.
• Right to work in the United States without visa sponsorship.
• Experience in agriculture, commodity, or manufacturing businesses.
• Experience with geospatial data.
• Experience in deep learning neural networks.
• Experience working in a cloud environment e.g., Amazon Web Services.
• Experience with Big Data development in Hadoop and Spark frameworks.

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