Quantitative Researcher - Energy Trading

Key Responsibilities:

• Design and implement advanced predictive models to forecast energy market trends and inform trading strategies.
• Build, curate, and maintain high-quality datasets by integrating diverse energy market data sources, including fundamental and real-time market inputs.
• Conduct in-depth research and analysis of energy market dynamics to support model development.
• Develop, test, and deploy production-level code for trading systems, predictive tools, and data pipelines.
• Optimize algorithms, models, and datasets for performance, accuracy, and scalability.
• Collaborate with the team to share insights and refine strategies, while owning your individual projects.

About You:

• Advanced degree (PhD preferred) in a quantitative field (e.g., Mathematics, Physics, Computer Science, Engineering, or similar).
• Hands-on experience in power or gas markets, or in forecasting key energy fundamentals such as solar and wind power production or demand.
• Expertise in predictive modelling, with a track record of developing accurate forecasting tools for financial or energy markets.
• Strong skills in building and managing complex datasets, including data sourcing, cleaning, and structuring for analysis.
• Advanced programming skills in Python, C++, and/or C#, with a focus on clean, efficient, and reliable code.
• Solid background in computer science and software development, including data structures, algorithms, and system design.
• Passion for computers and technology, with a proactive approach to learning and problem-solving.
• Ability to work independently in a fast-paced environment while delivering high-quality results.
• Excellent analytical skills and a rigorous approach to modelling, research, and data validation.
• Experience with large-scale data analysis or machine learning applications in trading.

What we can Offer You:

• Flat hierarchy and high levels of trust and autonomy
• Exciting problems to solve
• Collaborative team made up of really smart and curious people
• Nice office in Nordhavn with a hybrid work model
• Pension, Health Insurance and 30 days of vacation

Practicalities:

To apply, please send us your CV and a cover letter telling us why you think this role is a great fit for you. If your profile looks like a good match, we will get in touch to coordinate an online technical test as a first step in the interview process.

Should you have questions about the role that you would like clarified before applying, you're welcome to send an email to quant_jobs@alipescapital.com. Please note that applications should not be sent to the email address but rather via the job link.