We offer four types of experience in our internships:
• Data engineering: connecting, structuring and analyzing complex datasets
• Dashboarding: presenting datasets visually so they can be used in decision making throughout the business in an efficient way
• Master data improvements: analyzing gaps and inconsistencies in the key data needed to plan our company.
• Master data improvements: predictive and prescriptive mathematical models for a practical business context and implement them in our master data and tools & systems landscape.
Interns can be involved in one or multiple of the above points. We will place you based on your interest and skill set, and the current projects in our department. Our current applications are in Supply Chain (e.g. Inventory, Servicelevel, Cost), Supply Planning, Demand Planning, Material Planning, Logistics, and Manufacturing. Since you will be part of the global COE which deals with end-to-end processes, your solutions can result in a significant impact on our world-wide business. During development and implementation, you will collaborate with different functional teams. Together with these stakeholders, you will closely monitor the process outcomes to reach the desired performance improvement.
• Students need to be enrolled at a university in The Netherlands, or need to have EU citizenship and be enrolled at a university in Europe (incl. those studying at non-EU countries like Switzerland).
• Excellent knowledge of MS Office
• Experiences with Python (or similar programming languages)
• Curious to learn and able to dive into something new
• Able to focus on a task, follow through and “get things done”
• Excellent communication skills and the ability to understand and foster the interfaces with stakeholders
• An analytical, data driven, fact-based approach to problem solving
• Very good command of the English language
Nice to haves:
• In depth understanding of machine learning algorithms (Clustering, Neural Networks, Decision Trees)
• Previous internships in Business Planning, Supply Chain, or Manufacturing & Logistics.
A background in one of the following studies is strongly preferred: Data science, Mathematics, AI, Computer Science, Econometrics, Engineering, Technical BA, or Supply Chain Management / Business Administration with a strong background in technical aspects.
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