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Quantitative Analyst for Automated Trading

Danske Commodities A/S Århus, Danemark
Gepostet vor 6 Tagen Im Büro Permanent To be agreed
Would you like to a job with a direct impact on the performance of one of Europe’s leading energy trading companies? And does working with machine learning and tools supporting automated trading sound like fun to you? Then you might be our new quantitative analyst for our Automated Trading team.

Automated Trading at Danske Commodities (DC)

In Automated Trading, we support our business teams with developing, implementing and monitoring algo trading strategies. On a daily basis, we work with fundamentals such as weather and pricing data that affect the markets we trade in. We are driven by our common goal of making better and faster trading decisions, always pushing our strategies and analyses to new heights. And to be one step ahead, we always need to be aware of new developments within machine learning and algo trading.

You will join a team of skilled specialists ranging from economists, meteorologists, physicists and machine learning specialists. We are a team that set the bar high while always supporting each other – and we make sure to have fun as we go along. Besides working closely with skilled team members with diverse backgrounds, you will also get to work with stakeholders across the business, such as traders, software developers and data engineers.

Your journey as our new quantitative analyst

No matter your level of experience, we will make sure you get a thorough introduction to the team, your tasks, the power markets and how we work. Your first assignment will be to dive into our wide range of data and become familiar with our coding principles and algorithmic framework. After that, you will begin to partake in the development, implementation and monitoring of both current and new algo strategies. On the longer term, you will become responsible for your own area within our algo development – ranging from working with weather data, a specific geographical area to specific products. By using machine learning in your daily work, you will contribute to our automated trading setup, giving your work a direct impact on the performance of our trading business.

You’ll have the opportunity to push our trading strategies to the next level and be part of future-proofing the energy trading industry - Thor Kalstrup, Director, Head of Automated Trading.

We offer

  • professional and skilled colleagues, who set the bar high
  • great opportunities for individual development
  • flexible working hours, including the opportunity to work from home up to two days a week as per agreement with your direct leader
  • numerous social and professional events, incl. sporting events and parties
  • an office in the heart of Aarhus, next to the central train station


  • develop, implement and improve automated trading strategies
  • analyse weather, pricing and fundamental power market data
  • participate in building our algorithmic trading framework
  • actively take part in knowledge sharing and sparring across teams
  • work closely with Software Development and Data Engineering teams


We expect that you:

  • have a relevant educational background within Data Science, Computer Science, Engineering, Physics or similar
  • are an avid programmer with solid capabilities within data handling
  • have experience in working with machine learning
  • are experienced in Python or similar programming language
  • are proficient in English, both written and verbal

Personal skills

We expect that you:

  • are a logical thinker and mathematically well grounded – these are important traits when working with machine learning, strategy development and market understanding
  • are not afraid to take responsibility – you will eventually be responsible for your own strategies
  • see opportunities where other see problems – you need to approach problems proactively, since we are working with data in uncertain markets
  • can work analytically and in a structured manner – the products we deliver should be based on thorough, analytical work

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