Master Thesis Student (Data Science)

TL;DR

Master Thesis Student (Data Science): Developing a structured data approach for product-level carbon footprint assessments in semiconductor manufacturing with an accent on data modeling, relationship mapping, and query development. Focus on building prototypes to integrate fragmented industrial data and demonstrating functionality through a practical case study.

Location: Must be based in Hamburg

Company

hirify.global is a global semiconductor manufacturer focused on high-volume production of essential components.

What you will do

• Analyze existing manufacturing and product-level data to identify structures and relationships.
• Design a structured data model to organize product-relevant information.
• Explore and link data to support product-level carbon footprint analysis.
• Develop queries and small-scale prototypes to test the data model.
• Apply the model to a practical case study to demonstrate functionality and data integration.
• Document the design, methodology, and findings in a clear thesis report.

Requirements

• Enrolled Master’s student in Data Science, Engineering, Information Systems, or similar.
• Proven experience with data-oriented programming languages like Python.
• Basic knowledge of querying languages such as SQL or SPARQL.
• Experience with relational databases and data processing tools like pandas.
• Strong analytical and structured thinking skills.
• Good communication skills in English.

Nice to have

• Basic knowledge of graph-based data models.
• Basic knowledge of semiconductor products.
• German language skills.
• Interest in sustainability and life cycle assessments.

Culture & Benefits

• Hands-on experience with real industrial data in a complex manufacturing environment.
• Attractive remuneration and a bonus for a high-quality final thesis.
• Exposure to cross-team collaboration and exploratory project work.
• Potential opportunities for future employment after graduation.
• Inclusive work environment with access to various employee resource groups.