Quantitative trader

As a Quantitative Trader, you will find, build and run systematic strategies across the forward markets for gas and power. You decide what to trade and how to do it as long as you can back it with data and sound analysis. We succeed as a team, but you own your strategies, their risk and PnL.

More specifically, your responsibilities include:

• generating and testing new trading ideas across gas and power forwards, and identifying where the market is mispriced

• developing signals and models using machine learning and advanced quantitative modelling, and taking the most promising ones into production

• running your automated strategies in the market, including position sizing, execution set-up and ongoing performance monitoring

• owning the PnL and risk of your strategies within your mandate, scaling what works and shutting down what does not

• collaborating with traders, analysts and engineers to turn ideas into robust, scalable strategies

• continuously exploring new data, products and methods in the search for new sources of alpha

You will join our Forward Automated Trading team, which develops and operates systematic strategies in the European gas and power markets. We are expanding the team with two new colleagues, and you will have a real influence on our direction and strategy portfolio from the start.

You will work alongside colleagues with strong quantitative and engineering backgrounds, who provide a solid technical foundation. On top of that, you get the freedom to pursue your own ideas and the responsibility that comes with it.

As you will have a big say in our trading strategies, we imagine that you enjoy combining quantitative analysis with commercial judgement and taking responsibility for the outcomes. You are motivated by taking ideas all the way from hypothesis to live trading. We succeed as a team, so we also expect that you are a team player who likes to challenge ideas, discuss trading decisions and openly share what works and what does not.

Furthermore, we imagine that you:

• hold a MSc or PhD in statistics, economics, mathematics, physics, computer science, financial engineering or a related quantitative field

• understand financial markets and trading, including forwards and futures, curves and spreads, and risk and return

• have a solid foundation in applied statistics and machine learning, and know how to use it with sound commercial judgement

• can write clean, production-ready code in Python

• have experience with real PnL, for example from trading, a prop environment, a research desk or a serious personal project

• bring 4+ years of relevant experience from trading, quantitative research or a similar environment. We are equally interested in demonstrated expertise, and we would love to see your Kaggle profile, GitHub repositories or similar, if you are early in your career. We will tailor the role to your profile

Please note that prior knowledge of the energy sector is not required for this role.

You can read more about our recruitment process here. Please note that if you are an international candidate, we will reimburse travel expenses in connection with potential interviews and support you with the relocation process.

At Danske Commodities, we trade energy across 40+ markets and deliver solutions for energy producers and large-scale consumers.

Our people work together to find value in everything we do and deliver it. For our partners. And for the energy system as a whole. Together with our parent company Equinor, we operate on a scale few trading houses can match.

Our organisation is flat with an open-door policy. We expect you to care. About your work. About your colleagues. And about the difference we make.

Aspiring chefs, beekeepers, runners, parents, gamers – we’re proud of our diversity of ideas. What binds us together is that we all find average genuinely uncomfortable and want to do something about it.

We’re big on trust and providing the freedom for you to thrive. Together, we’ll make sure you’ll be the best version of you. Because happy employees perform better and we’re in this for the long run. No matter the stage in life you’re in, we’ve got you.

Join us. You'll love Mondays.