Master Thesis Student. Procurement Analytics & Material Intelligence
On-site · Zürich, Zurich, Switzerland
Job Summary
Master thesis student to support a global procurement analytics initiative by transforming technical material information such as SDS, PDS, specifications and item descriptions into a structured Material DNA and linking it with procurement data for clustering, benchmarking and negotiation support. Develop a first material intelligence framework, test clustering or data analysis approaches, and create practical outputs for procurement decision-making. Requires current master studies in a relevant field, strong analytical thinking, data science skills (Python, clustering, ML, visualization), understanding of chemistry/materials, and ability to translate technical information into business-relevant insights. Emphasizes a structured working style and capacity to handle incomplete data. Location: Zürich, Switzerland. Remote options: in-person.
Required Qualifications
- 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.
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