Intern Model risk

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

At a glance

At ABN AMRO, models play an important role in how we understand and manage credit risk. From estimating the probability that a customer may default, to calculating potential losses and provisions, these models help shape critical risk decisions across the bank.

At ABN AMRO, models play an important role in how we understand and manage credit risk. From estimating the probability that a customer may default, to calculating potential losses and provisions, these models help shape critical risk decisions across the bank.

Within the Retail and Non-Retail Credit Model Risk (CMR) teams, you will work on the validation of models that support a wide range of credit risk applications, including PD, LGD, EAD and provisioning models. You will join a specialised team of quantitative professionals who combine strong analytical thinking with practical implementation and sound risk judgement.

We are looking for a final-year master’s student in a quantitative field such as econometrics, quantitative finance, mathematics, physics or a related discipline, with a strong academic track record, an interest in credit risk modelling, and hands‑on experience with Python.

Your job

As an intern in the Retail and Non-Retail Credit Model Risk teams, you will be part of a highly skilled and collaborative environment where quantitative analysis, risk management and technology come together.

You will contribute to the validation of credit risk models and support the team in assessing whether models are conceptually sound, statistically robust and fit for purpose. Your work may include:

• 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 probability of default (PD), loss given default (LGD), exposure at default (EAD) and provision calculations
• helping structure documentation and supporting administrative tasks that are essential to sound model risk management

From early on, you will be encouraged to contribute actively, ask questions, and take ownership of your work. With guidance from the team, you will be expected to deliver meaningful contributions within the first weeks of the internship.

Your working environment

You will work as part of the Retail and Non-Retail Credit Model Risk teams in Amsterdam. Together, the teams consist of around 35 colleagues, including experienced quantitative professionals with backgrounds in mathematics, econometrics, physics and risk management.

The environment is intellectually sharp, collaborative and supportive. You will work closely with colleagues who are happy to share their expertise, challenge your thinking and help you grow. We work in a hybrid setup, combining office and remote work.

This is a team where analytical depth matters, but where communication, curiosity and collaboration are just as important.

Your profile

We are looking for a student in the final year of a master’s degree in a quantitative field, such as econometrics, (applied) mathematics, (applied) physics, quantitative finance or a similar programme, with a strong academic record.

You bring:

• enrolment in the final year of a master’s programme at a Dutch university
• strong quantitative and analytical skills
• a clear interest in credit risk models and quantitative modelling
• practical experience with Python, ideally including NumPy
• a understanding of statistics
• a 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
• a collaborative mindset and enjoyment in working as part of a team

Relevant extracurricular activities, international experience, and strong results in relevant quantitative courses (such as statistics and programming) are considered a plus.

The internship has a minimum duration of 3 months, with the possibility of extension up to 6 months.

What We Offer

An internship at ABN AMRO gives you the opportunity to apply your skills in a professional environment where your work is directly connected to real risk topics within the bank.

We offer:

• a meaningful internship within a highly specialised quantitative risk team
• the opportunity to learn from experienced professionals
• exposure to real model risk challenges in a large financial institution
• room to grow both personally and professionally
• a dynamic and intellectually stimulating working environment
• internship compensation in line with market practice