Senior Model Validation Quant

Danske Bank; København; On-site; DKK 274,000 - 410,000; Full time

Job summary

Danske Bank seeks a Senior Model Validation Quant to bridge quantitative validation with software engineering. You will validate credit risk models (PD, LGD, CF, IFRS 9) and build core validation software, configure Databricks workflows, and enable repeatable analyses.

Initial focus: ~70% model validation, ~30% tooling and infrastructure engineering, collaborating in a cloud-enabled environment with GitHub Copilot support.

Qualifications

• MSc or PhD in a quantitative discipline or equivalent practical experience.
• Strong coding practices in Python and SQL.
• Experience with Git and collaborative code reviews.

Responsibilities

• Perform and lead model validations for credit risk models (PD, LGD, CF, IFRS 9).
• Build and evolve validation software in Python; create reusable tools.
• Develop automated templates to generate evidence bundles and publish PDFs.
• Design and manage GitHub Actions CI/CD pipelines and Databricks Asset Bundles.
• Integrate AI-assisted coding to accelerate delivery and modernise codebases.
• Promote version control, code reviews, and reproducible analyses across the team.
• Present architectures and validation conclusions to developers, risk leaders, and regulators.

Skills

Python programming

SQL

Git version control

Databricks

GitHub Actions

AI tooling (GitHub Copilot)

Communication

Education

MSc or PhD in a quantitative discipline

Tools

Databricks

GitHub

GitHub Actions

Python packaging

Job description

Job Description

In Credit Risk Model Validation (CRMV), we are reimagining model risk management across Danske Bank, moving from manual data wrangling, ad hoc scripts, and copied notebooks towards an industrialised, reproducible, AI-accelerated quantitative engineering ecosystem.

To realise this vision, we are looking for a Senior Model Validation Quant who bridges quantitative model validation and software and infrastructure engineering. You will combine strong quantitative skills with sound engineering practices to validate models, build our core validation software, and configure modern cloud workflows.

Enabling the team to perform high-quality, repeatable validations is as important as running them yourself. Your initial focus will be roughly 70% direct model validation and 30% tooling and infrastructure engineering, adapting as our platform and automation mature.

You will join a skilled, collaborative, forward-thinking team of risk professionals migrating to GitHub Enterprise Cloud and Databricks, building modular internal Python packages, configuring Databricks Asset Bundles (DABs) and GitHub Actions CI/CD workflows, and using GitHub Copilot as a daily engineering partner.

What you will be doing:

• Perform and lead model validations: independently validate credit risk models (e.g. PD, LGD, CF, and IFRS 9), assessing conceptual soundness, statistical performance, and model limitations.
• Build and evolve validation software: design, implement, and maintain core Python packages and shared libraries that translate quantitative methodologies into clean, parameter-driven, testable tools.
• Enable the department: create tools and automated templates that help fellow validators run analyses, generate standard evidence bundles, and produce publication-ready PDF reports with minimal manual effort.
• Design modern workflows and infrastructure: set up and manage GitHub Actions workflows, CI/CD pipelines, and Databricks Asset Bundles (DABs) for automated, audit-ready execution across environments.
• Integrate AI-assisted engineering: use GitHub Copilot extensively each day to accelerate code delivery, write comprehensive test suites, and modernise legacy codebases.
• Promote engineering excellence: promote sound version control practices, structured code reviews, and reproducible analyses across the team.
• Engage key stakeholders: clearly and persuasively present technical architectures, quantitative findings, and validation conclusions to model developers, risk leaders, and regulatory counterparts.

About you:

• Quantitative grounding: you have an MSc or PhD, or equivalent practical experience, in a quantitative discipline (e.g. mathematics, statistics, computer science, physics, quantitative finance, data science, or engineering).
• Strong coding practices: you have solid practical experience writing clean, modular Python and SQL code.
• Collaborative version control (Git is essential): you are confident with Git branching strategies, pull requests, automated checks, and collaborative code reviews.
• Infrastructure and automation mindset: you have practical experience with, or a strong interest in learning, platforms such as Databricks (including DABs) and GitHub Actions.
• Enthusiasm for AI tooling: you are keen to use GitHub Copilot daily to enhance your workflow. Prior experience is a plus, but curiosity and openness to AI-assisted coding matter most.
• Bridge-builder mindset: you enjoy combining quantitative modelling with software engineering and switching between building infrastructure and exploring model mechanics.
• Clear communicator: you communicate clearly and warmly in English, translating technical and mathematical nuances into accessible insights for colleagues with varied backgrounds.

What we offer you:

This position can be located both in Denmark and Lithuania. If the position is located in Lithuania, the salary range will be from 3280 EUR to 4920 EUR gross (based on your competencies relevant for the job) and your contractual job title will be Risk Methodology & Model Validation.

If you have any questions, please contact Morten Gadegaard Jørgensen [e-mail]