- IFRS9 Expected Loss methodologies,This includes all inputs of Probability of Default, Loss Given Default and Exposure at Default (methodology).
- Credit scoring models (Retail loan origination models, behavioral scorecards).
- Strong quantitative education in area such as computer engineering, computer science, actuarial studies, statistics and economics.
- Experienced in programing languages suited for doing statistical and data analysis such as python, R or SAS.
- Strong knowledge of SQL.
- Strong knowledge of statistics and traditional machine learning.
- 2 years of experience at least in quantitative analysis, preferably within risk modeling in financial institution.
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