Data Scientist: Credit Risk Modelling (Remote-Friendly)

ABN AMRO Bank N.V.; Amsterdam; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Pension scheme

Flexible working from home

Five weeks vacation plus two mandatory

Development budget €1,000 per year

Annual public transport pass

Job summary

ABN AMRO Bank N.V. is seeking data scientist medior profiles to redevelop credit risk models for various lending portfolios. You will contribute across the model lifecycle, from initiation to internal validation and inspections by DNB/ECB, applying advanced statistics and coding skills.

The role involves collaboration with a diverse, international Risk Modelling team, with a focus on regulatory compliance and impactful risk-based decision making.

Qualifications

• Master's degree or PhD in a quantitative field required.
• >2 years experience in quantitative roles within a financial environment.
• Fluent English written and spoken; effective communicator with stakeholders at all levels.
• Familiarity with Spark, Python and SQL; experience with Azure DevOps / Git is a plus.

Responsibilities

• Redevelop credit risk models for diverse lending portfolios across the bank.
• Contribute to all phases of the model redevelopment cycle: from initiation to internal validation and regulatory inspections.
• Collaborate with stakeholders across the bank to articulate modelling choices and ensure alignment with regulations (Basel, CRR).

Skills

Strong communication

Stakeholder management

Modelling and statistics

Fluent English

Education

Master's degree or PhD in a quantitative field

Tools

Spark

Python

SQL

Azure DevOps / Git

Job description

ABN AMRO Bank N.V. is seeking data scientist medior profiles to redevelop credit risk models for various lending portfolios. You will contribute across the model lifecycle, from initiation to internal validation and inspections by DNB/ECB, applying advanced statistics and coding skills.

The role involves collaboration with a diverse, international Risk Modelling team, with a focus on regulatory compliance and impactful risk-based decision making.