I am looking for a Research Fellow at the University of Edinburgh for 6 months from July 2019 to work on an exciting project on stress testing for credit risk with SAS and Nationwide.
There is the possibility of working remotely.
Salary £23,350.75 for 6 months.
Please find below the details of the position.
If you are interested, feel free to email me.
Chancellor’s Fellow in Data Science
University of Edinburgh Business School
29 Buccleuch Place, EH8 9JS
T 0131 6511028
Job title: Research Fellow (6 months, full-time, fixed term)
School/Support Department: Business School
Unit (if applicable): Management Science and Business Economics
Line manager: Dr Raffaella Calabrese
To provide support to Dr Calabrese and Dr Belle in order to:
• elaborate a dataset provided by Nationwide;
• apply a machine learning technique proposed by Dr Belle to stress test a credit scoring model (see papers below);
• assist in the production of publications from this dataset, targeted at top outlets;
• develop activities on stress testing with SAS and Nationwide
Responsibility for applying and implementing an explainable machine learning method proposed by Dr Belle to stress test a credit scoring model
Application of the proposed method to the dataset provided by Nationwide to stress test a credit scoring model
• Principal Investigator –Dr Raffaella Calabrese, Chancellor’s Fellow in Data Science, Edinburgh.
• Dr Vaishak Belle -- Chancellor's Fellow in Human-like Computing and/or Software, Edinburgh
• Iain Brown -- Head of Data Science, SAS
• Matthew Jones -- Head of Retail Decision Modelling, Nationwide.
Knowledge, Skills and Experience Needed for the Job
MSc degree in Maths, Statistics, Informatics (or other numerical disciplines ) or Social Science
A knowledge of the machine learning techniques
Experience of quantitative analysis of data
Working knowledge of Python, Java, C++, R
Excellent personal, written and verbal communication skills
Ability to work independently and as part of a team
A PhD degree in Maths, Statistics, Informatics (or other numerical disciplines ) or Social Science
Knowledge in credit risk
Working knowledge of SAS
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