Nexperia Germany GmbH
22529 Hamburg - Deutschland
Data Scientist
Praktikum/Trainee/Werkstudent
Vollzeit
ab 15.04.2026
Beschreibung
**About this role**
You will work on structuring and connecting complex manufacturing data to support product-level sustainability analysis. For this you will work with real industrial data and collaborate with domain experts.
The focus is on:
1. Designing a logical data structure
2. Understanding how different data points relate to each other
3. Enabling data retrieval and analysis through queries
In this thesis, you will develop a structured data approach to organize and manage product-... weiter lesen
You will work on structuring and connecting complex manufacturing data to support product-level sustainability analysis. For this you will work with real industrial data and collaborate with domain experts.
The focus is on:
1. Designing a logical data structure
2. Understanding how different data points relate to each other
3. Enabling data retrieval and analysis through queries
In this thesis, you will develop a structured data approach to organize and manage product-... weiter lesen
**About this role**
You will work on structuring and connecting complex manufacturing data to support product-level sustainability analysis. For this you will work with real industrial data and collaborate with domain experts.
The focus is on:
1. Designing a logical data structure
2. Understanding how different data points relate to each other
3. Enabling data retrieval and analysis through queries
In this thesis, you will develop a structured data approach to organize and manage product-level data to support accurate Product Carbon Footprint (PCF) assessments in semiconductor manufacturing, which requires working with complex and fragmented data.
**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 data.
- 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 (proof-of-concept).
- Document the design, methodology, and findings in a clear and structured thesis report.
- Present results and insights to stakeholders in a concise and professional manner.
- Navigate uncertainty with analytical thinking and open-mindedness.
**What you will need**
- Enrolled Master’s student in Data Science, Engineering, Information Systems, or similar
- General understanding and passion for data
- Proven experience with data-oriented programming languages (e.g. Python, or similar) and basic knowledge of querying (e.g., SQL, SPARQL, or similar)
- Experience with relational databases and data processing (e.g. SQL, pandas-based ETL, or similar)
- Strong analytical, structured thinking, and problem-solving skills; able to explore solutions independently and show natural curiosity
- Good communication skills in English (German language skills beneficial) and ability to work independently
- Basic knowledge of graph-based data models (e.g. RDF/SPARQL, or similar) is a plus
- Basic knowledge of semiconductor products is a plus
- Interest in sustainability, life cycle assessments, product carbon footprints, or semiconductor manufacturing
You will work on structuring and connecting complex manufacturing data to support product-level sustainability analysis. For this you will work with real industrial data and collaborate with domain experts.
The focus is on:
1. Designing a logical data structure
2. Understanding how different data points relate to each other
3. Enabling data retrieval and analysis through queries
In this thesis, you will develop a structured data approach to organize and manage product-level data to support accurate Product Carbon Footprint (PCF) assessments in semiconductor manufacturing, which requires working with complex and fragmented data.
**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 data.
- 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 (proof-of-concept).
- Document the design, methodology, and findings in a clear and structured thesis report.
- Present results and insights to stakeholders in a concise and professional manner.
- Navigate uncertainty with analytical thinking and open-mindedness.
**What you will need**
- Enrolled Master’s student in Data Science, Engineering, Information Systems, or similar
- General understanding and passion for data
- Proven experience with data-oriented programming languages (e.g. Python, or similar) and basic knowledge of querying (e.g., SQL, SPARQL, or similar)
- Experience with relational databases and data processing (e.g. SQL, pandas-based ETL, or similar)
- Strong analytical, structured thinking, and problem-solving skills; able to explore solutions independently and show natural curiosity
- Good communication skills in English (German language skills beneficial) and ability to work independently
- Basic knowledge of graph-based data models (e.g. RDF/SPARQL, or similar) is a plus
- Basic knowledge of semiconductor products is a plus
- Interest in sustainability, life cycle assessments, product carbon footprints, or semiconductor manufacturing
Ref-Nr.: 10462649
Aktualisiert:
28.04.2026
Quelle: Bundesagentur für Arbeit
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Ob die Stelle noch verfügbar ist und weitere Informationen findest du direkt auf der Website der Bundesagentur für Arbeit. Bitte beachte: OPROMA ist nicht der Anbieter dieser Stelle und kann keine Auskünfte geben.
weitere Infos Rechtliche Hinweise zur Nutzung
Ob die Stelle noch verfügbar ist und weitere Informationen findest du direkt auf der Website der Bundesagentur für Arbeit. Bitte beachte: OPROMA ist nicht der Anbieter dieser Stelle und kann keine Auskünfte geben.
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