Data Scientist - Credit Risk Modelling

• An attractive gross monthly salary based on a 36-hour work week, including holiday allowanceand a flexible benefit budget.
• A job market allowance
• An excellent pension scheme, ensuring that you are well prepared for the future.
• Flexibility in working: working from home is possible in consultation with your team and depending on your role. We will provide an ergonomic home office setup for you.
• Plenty of room for relaxation with five weeks of vacation per year, supplemented by two mandatory days off. You can also purchase up to four additional weeks of vacation annually.
• Five “Banking for better days”: extra days off that you can use for personal development or volunteer work.
• Personal development is key: you receive a development budget of €1,000 per year, which can accumulate up to €3,000.
• An annual public transport pass with free public transportation throughout the Netherlands for both business and private use.

• You have >2 years experience working in a financial environment, in quantitative roles;
• You speak and write English fluently;
• You are an effective communicator, connecting easily with stakeholders on different levels of seniority;
• You are familiar with relevant coding languages, such as Spark, Python and SQL. Experience with Azure DevOps / git is a pre.
• You have thorough knowledge of banking and credit risk;
• You have thorough knowledge of rules and regulations and regulatory trends relevant for credit risk modelling (Basel, CRR, etc);
• Experience in working with DNB/ECB through communication and on-site inspections is a pre.
• Do you have what it takes to meet this challenge? Do you have experience with large projects with a strong quantitative character, and an eye for detail? Or are you a top talent in the field of quantitative risk management, and ready for the next step in your career? Look no further and apply to this role, we look forward to get to know you!

We are looking for new medior colleagues to join our Non-Retail Credit Risk Modelling team within ABN AMRO’s Risk Modelling department.

Effectively managing risks is essential in banking. The importance of modelling in core banking processes, such as risk management, is growing rapidly. New technologies, data sources, and data-driven solutions bring countless opportunities. These opportunities drive fierce competition and increasing regulatory demands on data and models.

ABN AMRO is taking a proactive step by leveraging these opportunities to strengthen its competitive position. The Risk Modelling department aims to create risk models that enable risk-based decision-making and sustainable growth. Our models comply with regulations, accurately predict risks, and allow us to offer clients a sustainable price that aligns with their risk profile. Our team is committed to being at the forefront and cutting edge of these developments.

As a data scientist in the Non-Retail Credit Risk Modelling department, you play a key role in redeveloping credit risk models for various lending portfolios. You and your team are central to reshaping ABN AMRO’s credit risk model landscape-one of the major challenges in the bank’s risk management. In this role, you contribute to every phase of the model redevelopment cycle, from model initiation to internal validation and onsite inspections by DNB/ECB. You have advanced knowledge of statistics, coding, modelling decisions, and applicable regulations. You can clearly articulate your views and foster strong collaboration with stakeholders across the bank.

ABN AMRO’s Risk Modelling department is a young and international team consisting of over 150 professionals from diverse backgrounds. As the bank’s centre of excellence for quantitative risk models, we play a crucial role in daily decision-making processes. Our models support activities like pricing deals, granting credits, setting market risk limits, and determining capital requirements. Our team thrives on intellectual challenges and has a hands-on mindset to deliver results. Collaboration is key to ensuring our work has maximum usability and a positive impact across the bank.