Credit Model Risk Intern: Validation & Python

ABN AMRO Bank N.V.; Amsterdam; Hybrid; EUR 11,000 - 16,000; Full time

Job summary

ABN AMRO Bank N.V. invites a final-year master’s student in a quantitative field to join the Retail and Non-Retail Credit Model Risk teams in Amsterdam as an intern. You will validate credit risk models and support assessments of conceptual soundness, statistical robustness and fit for purpose.

Expect a collaborative, hybrid work environment and active ownership from early on. You will analyse model foundations, work with Python-based data and tools, and contribute to PD/LGD/EAD validation,

Qualifications

• Enrollment in the final year of a Dutch university master's programme.
• Strong quantitative and analytical skills.
• Clear interest in credit risk modelling.
• Practical experience with Python, ideally including NumPy.
• Understanding of statistics.
• Proactive mindset and the confidence to speak up, contribute ideas and ask questions.
• Curiosity, eagerness to learn, and a structured way of working.
• Strong communication and interpersonal skills.
• Collaborative mindset and enjoyment in working as part of a team.

Responsibilities

• Analysing the mathematical and statistical foundations of credit risk models.
• Working with model-related data and Python-based tooling.
• Supporting independent challenger analyses to assess model performance.
• Contributing to validation work for models used in PD, LGD, EAD and provisioning.
• Helping structure documentation and supporting administrative tasks.

Skills

Quantitative skills

Python (NumPy)

Statistical knowledge

Team player

Communication

Education

Master's student in quantitative field

Tools

Python

NumPy

Job description

ABN AMRO Bank N.V. invites a final-year master’s student in a quantitative field to join the Retail and Non-Retail Credit Model Risk teams in Amsterdam as an intern. You will validate credit risk models and support assessments of conceptual soundness, statistical robustness and fit for purpose.

Expect a collaborative, hybrid work environment and active ownership from early on. You will analyse model foundations, work with Python-based data and tools, and contribute to PD/LGD/EAD validation,