Doctoral candidate (PhD student) in SME Credit risk platform development

Updated: 5 days ago
Deadline: 31 Jul 2020

This is a fully funded position for 3 years (extendable to an additional 4th year) connected to a partnership with Yoba, a Luxembourgish startup in the fintech business ( ). Therefore, the objectives of the PhD project are defined in accordance to the project directions, and also aligned with the research interest of Yoba towards their product development.

The project aims to develop models and methodologies to build a platform to assess the credit risk of small and medium sized enterprises (SMEs) using data analytics, thus allowing Yoba to make credit decisions quicker and more efficiently and thus increasing the overall availability of credit to the underserved SME sector in Luxembourg and other European markets where Yoba will operate. The technology behind this platform will be fully supported by data and machine learning models will be utilised to: i) extract information from unstructured data, ii) provide credit scoring, iii) make model drift analysis, and iv) make anomaly detection. Significant effort will be put on privacy aspects and explainable models.

The successful candidate will be supervised by Dr. Mats Brorsson (also Professor at KTH Royal Institute of technology) from the University of Luxembourg and with an industrial supervisor from Yoba, and join a strong and motivated research team lead by Prof.  Radu State. The candidate is also expected to spend 20-30% of her/his time at the Yoba premises in central Luxembourg.

The position holder will be required to perform the following tasks:

  • Contribute to the project “SCRiPT - SME Credit Risk Platform”
  • Carry out research in the predefined areas
  • Disseminate results through scientific publications
  • Present results in well-known international conferences and workshops

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