Data Scientist - Credit Risk Modelling (Remote)

ABN AMRO Bank N.V.; Amsterdam; Híbrido; EUR 61.000 - 95.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Salary & benefits

Pension plan

Home office

Vacation allowance

Extra vacation days

Personal development budget

Transport pass

Descripción de la vacante

ABN AMRO Bank N.V. is seeking a medior Data Scientist for its Non-Retail Credit Risk Modelling team. You will redevelop credit risk models across lending portfolios and drive collaboration with various stakeholders.

Your role covers the full model lifecycle, including validation and regulatory interactions with DNB/ECB. The team is international and focuses on data-driven risk solutions, leveraging statistics, coding, and strong regulatory knowledge to deliver robust risk models and sustainable

Formación

• Master's degree or PhD in a quantitative field.
• 2+ years’ experience in credit risk modelling (IRB, IFRS9, Stress testing or related).
• Fluent English (written and spoken).
• Strong communicator with stakeholders at different seniorities.
• Familiar with Spark, Python and SQL; Azure DevOps / Git is a plus.

Responsabilidades

• Redevelop credit risk models for lending portfolios across the bank.
• Lead or contribute to all phases of the model redevelopment cycle, from initiation to internal validation.
• Coordinate with stakeholders and support on-site inspections by regulators (DNB/ECB).
• Ensure modelling decisions align with Basel, CRR and regulatory trends.

Conocimientos

Statistics

Spark

Python

SQL

Azure DevOps

Git

Data visualization

Educación

Master's or PhD in a quantitative field

Herramientas

Azure DevOps

Git

Python

Descripción del empleo

ABN AMRO Bank N.V. is seeking a medior Data Scientist for its Non-Retail Credit Risk Modelling team. You will redevelop credit risk models across lending portfolios and drive collaboration with various stakeholders.

Your role covers the full model lifecycle, including validation and regulatory interactions with DNB/ECB. The team is international and focuses on data-driven risk solutions, leveraging statistics, coding, and strong regulatory knowledge to deliver robust risk models and sustainable