Educational Background: enrollment or recent completion of a degree in a quantitative/numerical field (e.g., mathematics, statistics, finance, economics).
Basic Understanding of Credit Risk Models: a strong interest in credit risk modeling and a basic understanding of credit risk concepts.
Analytical Skills: demonstrated analytical and problem-solving skills.
Programming Knowledge: familiarity with programming, such as Python, R, or similar languages would be a plus.
Communication Skills: effective communication skills, both written and verbal.
Team Player: ability to collaborate and work effectively in a team environment.
Positive Attitude: a positive and eager-to-learn mindset.
Language Proficiency: proficiency in English (B2 level or equivalent)
Obligations
Provide support to assess various credit risk models
Creation of validation reports
Collaboration with model owners and other stakeholders
Research new approaches in the field of machine learning, data analysis, validation, experimentation, statistics, etc.
Benefits
Opportunities for professional growth and development.
