About the Role
As an Algorithm Developer, you’ll work across the full lifecycle of algorithmic trading—from concept to live deployment. You’ll collaborate closely with researchers, developers, and traders to shape trading models, strengthen our technical platform, and bring new strategies to market. Your work contributes directly to commercial outcomes and the evolution of our trading capabilities.
Key Responsibilities
* Develop, test and validate trading strategies.
* Contribute to the creative process of designing new algorithmic trading concepts.
* Build and maintain the bespoke algorithmic trading platform.
* Support the full workflow from research to live trading.
* Develop internal tools and maintain data‑capture and storage solutions.
Location
This role is based out of one of our locations in Denmark: Copenhagen or Aalborg.
About the Team
We are a cross‑disciplinary commercial team consisting of top‑level people with diverse quantitative backgrounds, such as software engineers, computer scientists, mathematicians and physicists. We share a mission of spearheading research, development, deployment, and operation of trading algorithms intended for energy commodity markets.
We work in an open workspace where learning and professional growth are actively encouraged and required via participation in study groups, conferences, sparring, and engaging with peers across the entire organization.
About You
The ideal candidate has a few years of relevant experience. Your educational background is expected to be a Master’s or PhD degree in computer science, software engineering, or an equivalent field.
Qualifications
* Familiarity with object‑oriented programming and C# .NET.
* Talent and passion for software development.
* Up‑to‑date knowledge of new technologies and methods.
* Driven, commercially minded, and collaborative.
* Effective communication skills in English.
Advantage
* Quantitative skills within mathematics, data science, or statistics.
* Basic knowledge of trading, including order types and market microstructure.
* Experience working with large datasets across various database technologies.
* Experience with message‑bus architectures or streaming‑data environments.
* Knowledge of scripting languages and machine‑learning tools such as R, Python, Keras, or TensorFlow.
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