Full Description

Job Description

Are you an engineer with a solid quantitative foundation, or a quantitative analyst with interest in modern software development and engineering discipline? Join Credit Risk Model Validation at Danske Bank and help us build the most technologically advanced, automated credit model risk management department in the Nordics.

In Credit Risk Model Validation (CRMV), we are reimagining how model risk is managed across Danske Bank. We are moving away from manual data wrangling, ad-hoc scripts, and copied notebooks towards an industrialised, reproducible, and AI-accelerated quantitative engineering ecosystem. In this role you will bridge the traditional divide between quantitative model validation and software engineering, with your initial focus being roughly 70% tooling and infrastructure engineering and 30% direct model validation.

You will be part of a collaborative, forward-thinking team operating on a modern stack: migrating to GitHub Enterprise Cloud and Databricks, building modular internal Python packages, configuring Databricks Asset Bundles (DABs), setting up GitHub Actions CI/CD workflows, and embedding GitHub Copilot as a standard daily partner in engineering.

This position can be located in Vilnius, Lithuania or Copenhagen, Denmark. The relocation package isn't applicable for this role.

What You Will Be Doing

Build and evolve validation software: design, implement, and maintain core Python packages and shared libraries that turn complex quantitative methodologies into clean, parameter-driven, and testable tools.

Architect modern workflows & infrastructure: set up and manage GitHub Actions workflows, CI/CD pipelines, and Databricks Asset Bundles (DABs) to ensure seamless, automated, and audit-ready execution across environments.

Empower and enable the department: create the tooling and automated templates that allow fellow validators to run analyses, generate standard evidence bundles, and produce publication-ready PDF reports with minimal manual friction.

Perform and lead model validations: apply your quantitative insight to independently validate credit risk models (such as PD, LGD, CF, IFRS 9, etc.), assessing conceptual soundness, statistical performance, and model limitations.

Integrate AI-assisted engineering: make heavy daily use of GitHub Copilot to accelerate code delivery, write thorough test suites, and modernise legacy codebases.

Promote engineering excellence: champion version control hygiene, structured code reviews, and reproducible analytical practices across the entire team.

Engage key stakeholders: present technical architectures, quantitative findings, and validation conclusions clearly and persuasively to model developers, risk leaders, and regulatory counterparts.

About You

Quantitative grounding: you hold an MSc, PhD, or equivalent practical experience in a quantitative discipline (e.g. Mathematics, Statistics, Computer Science, Physics, Quantitative Finance, Data Science, or Engineering).

Strong software and coding habits: you have solid hands-on experience writing clean, modular Python and SQL.

Collaborative version control (Git is a must): you are completely at home with Git branching strategies, pull requests, automated checks, and collaborative code reviews are second nature to you.

Infrastructure & automation mindset: you have practical experience with (or a strong appetite to master) modern platforms like Databricks (including DABs) and GitHub Actions.

Enthusiasm for AI tooling: you are excited to leverage GitHub Copilot daily to supercharge your workflow (prior experience is a plus, but curiosity and openness to AI-assisted coding are what count).

The bridge-builder mindset: you enjoy the intersection of quantitative modelling and software craftsmanship, and you are comfortable switching between building infrastructure and digging into model mechanics.

Clear communicator: you communicate with clarity and warmth in English, translating technical and mathematical nuances into straightforward insights for diverse colleagues.

What We Offer You

If based in Lithuania, the monthly salary range would be from 3280 EUR to 4920 EUR gross (based on your competencies relevant for the job).

Additionally, each Danske Bank employee receives employee benefits package (benefits are only valid for Lithuania the same as the salary ranges) which includes

Growth opportunities: professional & supportive team, e-learnings, numerous development programs; (incl. professional certificates); 100+ professions for internal mobility opportunities.

Health & Well-being: a diverse, inclusive, work & life balance work environment; additional health insurance; mental well-being practices; partial psychologist counselling compensation; silence and sleep zones at the office; game rooms.

Hybrid working conditions: home office budget (after the probation period); modern Danske Campus workplace developed with anthropologist for the best employee experience.

Additional days of leave: for rest, health, volunteering, exams in higher education institutions, and other important activities. Moreover, for seniority with Danske Bank.

Monetary compensation package: accidents & critical diseases insurance; financial support in case of unfortunate events, travel insurance; IIIrd Pillar Pension Fund contribution.

See all the benefits HERE.

Your title in job contract will be Risk Methodology & Model Validation.

If you're interested in this role and joining my team, feel free to contact me – Linas Smalakys, Head of Credit Risk Model Validation 3 via Linkedin and I will answer your questions!