New ways to measure the credit health of UK business
The Financial crisis suffered from the use of current risk models that were poor at predicting company death rates and that were black box credit risk models (e.g. Experian’s commercial Delphi score). There is a need for a more open environment to compare credit risk models.
The project will further the understanding of the range of risk models being used, using the data sets we have to understand the variety of risk models available. We expect the intern to help develop algorithms to track and predict company behaviour that capitalises on current models and incorporates additional new data sets to help users make more informed decisions. Part of the project will also involve building aggregate model algorithms to measure the health of UK business.
An ideal candidate will have a strong background in time series analysis, and statistics. Experience of at least one and preferably two of C, C++, C#, php, Java, Perl, S-PLUS/R or Matlab is essential. Other experiences that are not essential but highly useful are economics, digital signal processing, reinforced learning algorithms, portfolio theory. Some knowledge of finance theory and company accounts is desirable but training will be provided if necessary.
This internship is being offered by a Venture Capital backed start up and is based in London.
To apply, please send a CV and a cover letter to Lorcan Mac Manus, lbmm (at) industrialmaths.net
You may also contact Lorcan for informal enquiries about the post.
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