Master Thesis Student. Procurement Analytics & Material Intelligence

About the role

We are looking for a Master thesis student with a background in business, chemistry/material science and data science to support a global procurement analytics initiative. The thesis will explore how technical material information such as SDS, PDS, specifications and item descriptions can be transformed into a structured Material DNA and linked with procurement data for clustering, benchmarking and negotiation support. The student will work on one selected pilot category, develop a first material intelligence framework, test clustering or data analysis approaches, and create practical outputs for procurement decision-making. Current Master studies in a relevant field, e.g. Business Chemistry, Chemical Engineering, Industrial Engineering, Data Science, Business Analytics or similar. Good understanding of Chemistry, Materials or technical product specifications. Strong analytical thinking and interest in procurement, supply markets and business impact. Basic to good data science skills, e.g. Python, data cleaning, clustering, text analysis, machine learning or data visualization. Ability to translate technical information into business-relevant insights. Structured working style and ability to handle incomplete or imperfect data. We offer competitive salaries, aligned with local market benchmarks and the specific scope and responsibilities of each role. Compensation is determined based skills relevant to the position, education and/or training. We are committed to fair and equitable pay practices in accordance with applicable laws and regulations.

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Company Intel

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