• Lead and support colleagues responsible for checking model data quality model development (methodology and design) checking model performance and reporting issues to management and the steering committees.
  
• Develop and document high quality credit risk models including probability of default exposure at default and loss given default (PD EAD and LGD) including challenger models based on different modelling techniques (for instance but not limited to machine learning models).
  
• Implement the models into the banks model framework using Python.
  
• Work with Finance Treasury and Tech teams to source the relevant data and check consistency.
  
• Develop tests estimation and calibration procedures for forecasting models
  

• Significant experience of wholesale modelling (probability of default exposure at default and loss given default models (PD EAD and LGD) with an understanding of how models are implemented and used.
  
• Demonstrated ability to lead and support Model Development projects and an understanding of the endtoend model development as part of the model lifecycle process
  
• Understanding and familiarity with Regulation Requirements primarily UK (PRA) and EU (EBA/ECB) based regulation.
  
• Proficiency in manipulation of large data sets and excellent understanding of credit risk related data
  
• Demonstrated ability to explain technical tasks and methodology to a wider sometimes nontechnical audience.
  
• Comfortable working with stakeholders of various levels and the ability to adapt your communication style accordingly
  
• M.Sc. or Ph.D. in computer science statistics math finance econometrics or similar field
  
• Hands on programming experience in Python building financial or statistical models. Python experience should include model implementations handling large datasets.
  
• PLEASE NOTE: Candidates who do not have direct experience of Corporate Wholesale/Credit Risk & Model Development will not be considered
  
  

Procurement, vendor management, supply chain, sourcing