Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Communication @ 6
Mathematics @ 3
Python @ 3
Statistics @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
At ABN AMRO, models play an important role in understanding and managing credit risk. The Retail and Non-Retail Credit Model Risk teams validate models used for probability of default (PD), loss given default (LGD), exposure at default (EAD), and provisioning.
Responsibilities
- Analyse the mathematical and statistical foundations of credit risk models.
- Work with model-related data and Python-based tooling.
- Support independent challenger analyses to assess model performance.
- Contribute to validation work for PD, LGD, EAD, and provision calculation models.
- Help structure documentation and support administrative tasks related to model risk management.
- Contribute actively, ask questions, and take ownership of assigned work.
Requirements
- Final-year master's student at a Dutch university in a quantitative field such as econometrics, applied mathematics, applied physics, quantitative finance, or a related discipline.
- Strong academic record.
- Strong quantitative, analytical, and statistical skills.
- Interest in credit risk models and quantitative modelling.
- Practical experience with Python, ideally including NumPy.
- Proactive mindset, curiosity, eagerness to learn, and a structured way of working.
- Strong communication and interpersonal skills.
- Collaborative mindset and ability to work as part of a team.
- Relevant extracurricular activities, international experience, and strong results in statistics and programming courses are a plus.
The internship has a minimum duration of 3 months, with the possibility of extension up to 6 months.
Working Environment
You will work in the Retail and Non-Retail Credit Model Risk teams in Amsterdam. The teams consist of approximately 35 colleagues, including quantitative professionals with backgrounds in mathematics, econometrics, physics, and risk management. The role follows a hybrid setup combining office and remote work.
Benefits
- Meaningful internship within a specialised quantitative risk team.
- Opportunity to learn from experienced professionals.
- Exposure to real model risk challenges in a large financial institution.
- Opportunities for personal and professional development.
- Dynamic and intellectually stimulating working environment.
- Internship compensation in line with market practice.
- Internship compensation of €750 per month.
Applications must include a CV, cover letter, and grades in either the CV or cover letter.