About the Opportunity

The Ericsson Wallet platform is the Ericsson award winning banking product and one of the few fintech Ericsson products that is profitable on the financial market today.
Bank back-office customer market operations provide 24/7 support with dedicated teams and established processes. This setup is continuously monitored using predefined KPIs and regularly enhanced through product and process improvements.

What You Will Do

This thesis is divided into several steps with the end goal of showing a prototype of how the 24/7 way of working can be optimized using log consolidation and machine learning to create a searchable data set based on the current state of a Ericsson Wallet Platform installation.
Phasis in thesis work:
• Investigate and compare current research covering different types of trouble shooting using system logs.
• Implement at least one coding scheme and test using simulation or real test equipment.
• Analyse results of the tests and evaluate improvements using a log search assistant compared to existing tooling.
Relevant experience includes coursework or internships involving real-world datasets and AI analysis, along with familiarity with tools like Python, SQL, and basic data visualization libraries for data-driven insights.

The Skills You Bring

• Pursing MSc degree in AI/ML and Software Engineering
• Excellent presentation, communication and collaboration skills with a proven drive for results.
• The ideal candidate should have a foundational understanding of artificial intelligence.
• Experience in setting up a data analysis flow using open-source tools such as vector databases: ChromaDB and FASIS and AI-model tooling: LLAMA-3 (meta) and MistraL is a merit.
• Skills in programming using python, java script and one other typed programming language like java/C++/Go or similar, extra-curricular programming skills acquired outside the university is a merit.