4d ago

Master Thesis - Building Knowledge Graphs and Creating Queryable Data Warehouses Through LLM Methodology for Supply Chain Intelligence

Sweden - Lundmid

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Job TitleMaster Thesis - Building Knowledge Graphs and Creating Queryable Data Warehouses Through LLM Methodology for Supply Chain Intelligence Job Description Category Computer Science,

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Master Thesis - Building Knowledge Graphs and Creating Queryable Data Warehouses Through LLM Methodology for Supply Chain Intelligence

Computer Science, Data Engineering, Data Science

Master Thesis 30 hp

2 students completing 30 credits each

Axis Communications operates a complex global supply chain with multiple data sources, including ERP, CRM, financial, and manufacturing systems, logistics platforms, internal applications, etc. Currently, querying this distributed data requires deep technical knowledge of our data warehouse architecture, SQL expertise, and familiarity with our schemas. Business stakeholders with limited familiarity on data warehouse architecture may struggle to gain quick insights into critical questions that require data across different systems.  Domain experts within our supply chain organization possess deep knowledge of our supplier ecosystem, distributor networks, and their complex relationships. However, this knowledge usually exists in documents, spreadsheets, and institutional memory—not completely in a structured, queryable format that can enhance our data systems.

Answer these questions:

How do we capture this expert knowledge as a structured knowledge graph that enables an LLM to ask intelligent questions against our data warehouse?
Can a properly constructed knowledge graph—enriched with supply chain domain semantics—outperform simpler approaches like improved schema documentation for enabling natural language querying and impact analysis?

For this thesis proposal, we are seeking two students with a strong technical foundation and genuine interest in the intersection of data engineering, knowledge representation, and AI-driven data access.

Ideal Profile:

You are studying a Master Program in Computer Science, Technical Physics, Mathematics, Industrial Engineering, or equivalent technical discipline

You have strong fundamentals in data structures, algorithms, and software engineering principles

You have experience with Python and SQL, you're comfortable writing complex queries and data transformation scripts

You have experience with Git and GitHub for version control and collaborative development

You have experience with knowledge graphs or graph databases (Neo4j, ontologies, RDF, property graphs)

You are passionate about solving real-world data challenges and enjoy working with large, complex datasets

You are highly motivated, work well in pairs and enjoy collaborative problem-solving

You are eager to learn emerging technologies and can quickly adapt to new tools and frameworks

It’s a plus if you have:

Familiarity with DBT (Data Build Tool) or similar data transformation frameworks

Understanding of LLMs, prompt engineering, or retrieval-augmented generation (RAG)

Basic understanding of supply chain concepts or domain-driven design principles

Experience with API development (REST, GraphQL)

Karla Marie Paredes, karla.marie.paredes@axis.com.

Thesis Worker (Fixed Term)

2026-11-15

Certain roles at Axis require background checks, which means applicable verifications will be done in these recruitments. Notice will be provided before we take any action.

We enable a smarter, safer world by creating innovative solutions for improving security and business performance. As a network technology company and industry leader, we offer solutions in video surveillance, access control, intercom, and audio systems, enhanced by intelligent analytics applications.

With around 6000 committed employees in over 50 countries, we collaborate with partners worldwide. Together, we thrive in our friendly, open, and collaborative culture and inspire each other to think beyond the expected. United by our commitment to inclusion, diversity, and sustainability, we consistently seek to develop our skills and way of working.

For more information about Axis, please visit our website www.axis.com.

Listen to Get To Know Axis – Podcast