Master Thesis Worker - From Data Exploration to Scalable Engineering Practices

Building Tools for Learning Across the Product Lifecycle 

Thesis work is an excellent way to get closer to Scania and build relationships for the future. Many of today's employees began their Scania career with their degree project.

 

Background

 

TRATON GROUP is one of the world’s leading commercial vehicle manufacturers, with brands including Scania, MAN, International and Volkswagen Truck & Bus. Its portfolio covers light commercial vehicles, trucks and buses, complemented by financing, charging and digital logistics services. Through its global operations, production sites and extensive sales and service networks, TRATON has access to diverse vehicle platforms, real-world operational data and fleet deployment environments. This provides a strong foundation for developing and validating innovative solutions for sustainable and efficient transportation. 

 

We are a cross-functional enablement team within TRATON R&D, responsible for data platforms, AI strategies, and human-centered technology development. Our mission is to empower R&D engineers to use trustworthy data and smart tools to make faster, better decisions. You’ll work closely with experts in AI, product development, and data engineering– in a context where your research can directly shape the way we build the future of transportation.

 

Target Scope

Modern vehicle development relies on large and complex datasets from vehicles, tests, and simulations. Among the challenges are high-resolution time series, where visualisation is both a technical and a human-centred problem. How can we help experts quickly understand what is happening, detect deviations, and retain the context needed to draw sound conclusions?

Job Description

 

• Conduct a pre-study and formulate one or more research questions within visual analytics, interactive visualisation, or visualisation of vehicle, test or simulation data for an engineering context in line with the points below.
• Investigate methods for indexing, filtering, aggregating, and reducing large high-resolution time-series datasets at the level of detail required by the user's current question or view.
• Explore and prototype web-based interactive visualisations that preserve important patterns, deviations, and events, while supporting navigation from overview to detailed analysis and, when needed, raw data.
• Evaluate the proposed approach with R&D experts and assess trade-offs between responsiveness, scalability, analytical depth, and usability. Optionally investigate how GPU acceleration can support interactive interfaces for complex time series.

 

Who You Are

• You are curious about how large and complex datasets can be made understandable and useful.
• You want to combine technical problem-solving with a human-centred perspective and are motivated by creating tools that help engineers understand data, discover deviations, and make well-founded decisions.
  
• You are enrolled in a Master's program in computer science, data science, human-computer interaction, software engineering, or a related field.
• You have an interest in, and some experience with, interactive visualisation, visual analytics, data engineering, or high-resolution time-series data.
• You have programming experience and are willing to work across the data pipeline, for example using Python, SQL, and/or web technologies.
• You are analytical, structured, and able to communicate with both technical specialists and engineering domain experts.
• You are interested in balancing technical performance with the user's need for context, clarity, and an intuitive analytical experience.

 

 

Contact persons and supervisors 

If you have questions or would like further information, please contact:

Sarah Hantosi Albertsson

Head of Global Analytics Enablement

sarah.hantosi.albertsson@scania.com

 

Annette Hultåker, Technical Manager

annette.hultaker@scania.com

 

We look forward to your application!