Intern supporting data-driven optimization of procurement processes at BMW. Involvement in AI solutions and historical data analysis related to automotive components in Munich.
Responsibilities
Support in analyzing and preparing historical tender data.
Contribute to developing a formal definition of the term "bundling".
Contribute to the quantitative reconstruction and evaluation of past bundling practices.
Support the comparison of current practice with the existing deterministic model.
Assist in identifying and classifying relevant features such as component attributes, degree of industrialization, and modular system affiliation.
Support the development of an AI model approach based on bundling decisions.
Assist in evaluating model performance compared to historical decisions and the deterministic model.
Requirements
Currently enrolled in a degree program in Industrial Engineering, Business Informatics, Mechanical Engineering, or a comparable field.
Solid knowledge of data analysis, machine learning, and AI.
Analytical and structured mindset.
Interest in industrial procurement processes and technical product classification.
Ability to present complex topics clearly.
Good German and English skills.
Benefits
Comprehensive mentoring and onboarding.
Personal and professional development.
Flexible working hours.
Remote work options.
Attractive and fair compensation.
Student apartments (subject to availability; Munich location only).
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