Quantitative Developer

About the Opportunity: Koda Staff is partnering with a leading systematic investment manager that combines technology, quantitative research and data science to build sophisticated trading strategies across global financial markets. This is an opportunity to join a highly collaborative quantitative engineering team working alongside Researchers, Traders and Cloud Engineers to develop the technology that powers research, analytics and live trading. The environment is fast-paced, highly technical and focused on solving complex problems through engineering excellence and data-driven decision making. If you're passionate about Python, quantitative development and building scalable data platforms, this could be an excellent next step in your career. The Role: As a Python Quantitative Developer, you'll play a key role in designing and developing production-grade applications and research infrastructure that directly supports quantitative research and trading activities. Working closely with researchers and trading teams, you'll build scalable software, quantitative tools and cloud-native data platforms that enable better investment decisions. Responsibilities: Design, develop and maintain cloud-native Python applications supporting quantitative research and trading workflows. Build applications including: Market data dashboards Risk analytics Profit & Loss reporting Weather analytics Performance analysis tools Develop quantitative tooling, including: Backtesting frameworks Optimisation libraries Pricing libraries ETL pipelines Build and maintain scalable data pipelines for both research and production environments. Integrate, validate and process large alternative datasets Monitor, troubleshoot and continuously improve existing research and trading infrastructure. Collaborate closely with Quantitative Researchers, Traders and Engineering teams to deliver high-quality production software. What We're Looking For: 3+ years of commercial Python development experience. Strong knowledge of Python and numerical computing libraries, including: NumPy, Pandas, Polars, Xarray A strong quantitative mindset with an interest in financial markets and systematic trading. Experience building scalable production software. Experience developing ETL pipelines and processing large datasets. Strong understanding of software engineering best practices, including: Git, Automated testing, Packaging, CI/CD and deployment Experience working with relational databases such as PostgreSQL. Knowledge of object storage technologies.# Comfortable working independently while collaborating with both technical and business stakeholders. If you are located in Aarhus and this sounds like you, please apply directly.