Quantitative Developer: AI‑Powered Market Platform

Nykredit Group; København; Hybrid; DKK 700,000 - 900,000; Full time

Job summary

Nykredit Markets is seeking a Quantitative Developer to design and maintain analytics applications and quant infrastructure for pricing, risk, and modeling across asset classes. You will work with traders, sales, and engineers to deliver robust, scalable solutions and explore AI-enabled improvements.

Join the QS Financial Engineering team to advance Dragonfly and related tools, while collaborating across the department to ensure best-in-class models and decision-support for markets and clients.

Qualifications

• Degree in finance, economics, IT, natural sciences, or engineering.
• Strong software development skills incl. Python.
• Interest or experience with AI or machine learning.
• Familiar with generative AI, LLMs, AI agents, or modern AI tools.
• Understand software architecture, data structures, algorithms, and distributed systems.
• Analytical, able to solve complex financial and technical challenges.
• Effective communication and collaboration with technical and non-technical stakeholders.

Responsibilities

• Design and develop analytics applications for pricing, risk, and modeling of markets and instruments.
• Build scalable, robust quant infrastructure with CI/CD pipelines and monitoring.
• Monitor and optimize production data flows and model operation.
• Explore AI use cases and translate into business value for Markets.
• Tackle complex quantitative and technical challenges and deliver improvements.

Skills

Python

AI/ML

Distributed systems

CI/CD

GitHub Actions

Azure

Education

University degree in finance/economics/IT/engineering

Job description

Nykredit Markets is seeking a Quantitative Developer to design and maintain analytics applications and quant infrastructure for pricing, risk, and modeling across asset classes. You will work with traders, sales, and engineers to deliver robust, scalable solutions and explore AI-enabled improvements.

Join the QS Financial Engineering team to advance Dragonfly and related tools, while collaborating across the department to ensure best-in-class models and decision-support for markets and clients.