Credit Risk Quant Modeller - PhD/MSc Statistics
My client a Tier 1 Investment Bank are looking to recruit a Statistical Modeller to join The Quantitative Analytics group.
* Develop, document, and calibrate credit risk models in line with regulatory requirements, e.g. Basel, IFRS9
* Enhance model management through automation and development of new approaches
* Develop new credit risk models, managing the development through approval
* Validate performance of new models
* Document new models to required standards
* Maintain open dialogue with other modellers and validation teams on model developments and reviews
* Post graduate degree in a quantitative discipline, Mathematics, Statistics, Physics, Engineering, Econometrics. Statistics PhD or Masters would be the desired qualification.
* Very strong knowledge of statistics, e.g. regression analysis, reject inference, decision trees, cluster & time-series analysis
* Strong numerical programming ability using R and/or Python; working experience with SQL
* Track record of producing high quality written communication including results of research and presentations for technical and non-technical audiences
* Experience of developing and applying statistical models within credit risk domain
* Understanding of the quantitative techniques used in developing and validating PD, LGD, and/or EAD models
* Strong stakeholder management skills, with experience from complex projects
* Good project and people management skills; ability to motivate team and deliver within tight deadlines