Description
As a Data Scientist in the Credit Risk Models team at National Bank, you’ll be acting as an expert in credit risk modelling to develop and deploy models to assess the credit risk of the bank's Personal and Commercial customers. It means applying rigorous statistical and financial analysis methods on large databases to find the risk factors that will make it possible to quantify the credit risk associated with each borrower. It also means monitoring the performance of all the models in place. It will be through your autonomy, your rigor and your spirit of initiative that you will stand out.
Your role:
- Develop PD, LGD and EAD regulatory models following a rigorous and documented approach
- Perform quantitative personal and business portfolio analysis
- Explain and defend the models developed with internal partners and regulatory authorities
- Actively participate with IT partners and business lines to ensure the understanding and implementation of the models developed
- Monitor the performance of models developed using recognized statistical measures (backtesting)
Your team:
Within the Credit Analytics and Climate Risks sector, you are part of a vice-presidency of about a hundred colleagues and a team of four expert colleagues. You report to the Director - Analytics - Credit Risk Models. Our team stands out for its varied expertise in credit risk and quantitative methods. You have a flexible and hybrid working environment.
Prerequisites:
- Bachelor's degree related to the industry (mathematics, statistics, econometrics, financial engineering, etc.) and 3-5 years of relevant experience or Master's degree related to the industry and 1-3 years of relevant experience
- Experience in statistical and probabilistic modeling
- Good programming knowledge, preferably SAS or SQL
- Knowledge of the Basel Accord and IFRS9 is an asset
- Good writing skills (technical documentation, PowerPoint presentation)