Master Thesis Worker - From Data Exploration to Scalable Engineering Practices

Vehicle development generates extensive, high-resolution time-series data from vehicles, testing and simulations. This thesis explores how interactive visualisation can help R&D engineers identify patterns and deviations without losing the context needed for reliable conclusions. The work takes place within TRATON R&D’s cross-functional team for data platforms, AI strategies and human-centred technology.

The assignment

• Carry out an initial study and define research questions concerning visual analytics or interactive visualisation of engineering data.
• Investigate indexing, filtering, aggregation and data-reduction methods that adapt large time-series datasets to the user's current question or view.
• Develop web-based visualisation prototypes that retain meaningful patterns and events and allow users to move from an overview to detailed analysis and, where necessary, raw data.
• Evaluate the approach with R&D experts, comparing responsiveness, scalability, analytical depth and usability.
• Optionally explore GPU acceleration for interactive interfaces handling complex time series.

Who we are looking for

• Currently studying for a master's degree in computer science, data science, human-computer interaction, software engineering or a related discipline.
• Interested in making complex datasets understandable and combining technical development with user needs.
• Some experience in interactive visualisation, visual analytics, data engineering or high-resolution time-series data.
• Programming experience and willingness to work across the data pipeline, potentially using Python, SQL or web technologies.
• An analytical, organised approach and the ability to communicate with technical specialists and engineering experts.
• Interest in balancing computational performance with clarity, context and intuitive data exploration.

What we offer

• Close collaboration with specialists in AI, product development and data engineering.
• An R&D setting where thesis findings can influence future engineering tools and working practices.
• An opportunity to establish professional connections within Scania.

Practical details

Location: Södertälje. Include a CV, cover letter and academic transcript in your application. The advertised application period ends on 26 November 2026. Interviews take place on a rolling basis, and recruitment may close early. Questions: Sarah Hantosi Albertsson, Head of Global Analytics Enablement, sarah.hantosi.albertsson@scania.com; Annette Hultåker, Technical Manager, annette.hultaker@scania.com.