30 credits – Optimisation of data science algorithms i Sodertalje

Thesis project at Scania is an excellent way of making contacts for your future working life. Many of our current employees started their career with a thesis project. This thesis is within the data science team at Scania IT and you will be working within a field of great strategic value for Scania.

Background:

Scania is now undergoing a transformation from being a supplier of trucks, buses and engines to a supplier of complete and sustainable transport solutions. One big change on this journey is that Scania has to become a Data Driven Company, meaning utilizing our data assets in a more extended way to find new knowledge and use it in decisions, predictions, process improvement, strategic planning and more. Today we are extracting a lot of data from our vehicles and IT-systems to our Data Lake.

Target:

When the use of data science method increases, so does the need for optimisation of them. Evolutionary algorithms seem very promising and we would like for the thesis to focus on how these compare to more conventional optimisation techniques.

Assignment:

To compare different methods for optimisation of data science algorithm in the existing environment at Scania.

Education:
Specify education or specialisation: master student in IT or statistics, data science or similar.

Knowledge in the following subjects would be beneficial: Big data, Hadoop and related technologies, data mining, machine learning, optimisation, statistics and programming.

Number of students: 1-2
Start date: January 2019
Estimated time needed: 20 weeks

Contact persons and supervisors:

Isolde Snellman, IXAD, 08-553 71 117

Annette Hultåker, IXAD, 08-553 82 097