Senior Quant Model Validation & Engineering Lead

Danske Bank; København; On-site; DKK 500,000 - 751,000; Full time

Benefits offered by this job

Growth opportunities

Health & Well-being

Hybrid working conditions

Additional leave

Job summary

Danske Bank is expanding its Credit Risk Model Validation (CRMV) team in Copenhagen or Vilnius. You will bridge quantitative modelling and software engineering, focusing on tooling and infrastructure (~70%) and direct model validation (~30%).

You will work with Python, SQL, Databricks, and GitHub Actions, embedding Copilot and driving reproducible, audit-ready workflows across environments.

Qualifications

• Master's or PhD in a quantitative field or equivalent practical experience.
• Strong programming in Python and SQL; modular, testable code.
• Experience with Git workflows, code reviews, and CI/CD practices.

Responsibilities

• Build and evolve validation software: core Python packages and libraries.
• Architect modern workflows: CI/CD pipelines and Databricks Asset Bundles.
• Create tooling to enable validators to run analyses and generate reports.
• Perform and lead model validations for credit risk models (PD, LGD, CF, IFRS 9).
• Integrate AI tooling (GitHub Copilot) to accelerate delivery.
• Promote engineering hygiene and reproducible analyses across the team.
• Present architectures and validation findings to stakeholders.

Skills

Quantitative discipline MSc/PhD

Software development mindset

Git collaboration

Education

MSc/PhD in Mathematics/Statistics/CS/Physics/Quant Finance/Data Science/Engineering

Tools

Python

SQL

Databricks

GitHub Actions

GitHub Copilot

Git

Job description

Danske Bank is expanding its Credit Risk Model Validation (CRMV) team in Copenhagen or Vilnius. You will bridge quantitative modelling and software engineering, focusing on tooling and infrastructure (~70%) and direct model validation (~30%).

You will work with Python, SQL, Databricks, and GitHub Actions, embedding Copilot and driving reproducible, audit-ready workflows across environments.