Credit Risk Stress Testing Lead (Hybrid + AI)

Nordea; Helsinki; Hybrid; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Hybrid working model

Diversity and inclusion

Job summary

Nordea is seeking a Senior/Quantitative Risk Analyst to elevate Credit Risk Stress Testing by leveraging new models and data sources. The role can be based in Helsinki, Oslo, or Stockholm, with a hybrid work model and collaboration across Nordic capitals.

You will execute credit risk and climate stress tests, work with large datasets using SAS, Python, and MS SQL, and build data pipelines and analytical tools including AI-enabled capabilities. Strong communication and teamwork are essential.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field and fluent professional English.
• Strong analytical and technical skills for working with large, complex datasets.
• Ability to deliver high-quality work on time in a fast-paced environment.
• Ability to communicate complex data analyses to various stakeholders.
• Proactive, independent worker who also shares knowledge with others.

Responsibilities

• Execute credit risk and climate stress tests using new models and data sources.
• Operate on large data sets with SAS, Python and MS SQL.
• Build/maintain an adequacy testing framework with thorough documentation.
• Develop data pipelines and AI-enabled analytics tools; integrate new capabilities into analysis and reporting.
• Set requirements for data and model development; test capabilities and integrate into reporting.

Skills

Analytical skills

Technical data handling

Communication of data

Independent with teamwork

AI/ML experience

Education

Bachelor’s or Master’s in quantitative field

Tools

Python

SAS

SQL

Job description

Nordea is seeking a Senior/Quantitative Risk Analyst to elevate Credit Risk Stress Testing by leveraging new models and data sources. The role can be based in Helsinki, Oslo, or Stockholm, with a hybrid work model and collaboration across Nordic capitals.

You will execute credit risk and climate stress tests, work with large datasets using SAS, Python, and MS SQL, and build data pipelines and analytical tools including AI-enabled capabilities. Strong communication and teamwork are essential.