Energy Markets Quantitative Analyst – Student Intern

Norlys Energy Trading A/S; Aalborg; On-site; DKK 100,000 - 134,000; Part time

Benefits offered by this job

Hands-on energy trading experience

Job summary

Norlys Energy Trading A/S in Aalborg invites applications from motivated students to join the Physical Asset Management team. You will develop quantitative solutions to optimise energy assets in real time and support trading algorithms.

The role offers hands-on experience in a professional energy trading environment, collaboration with experienced colleagues, and a chance to apply academic knowledge to real-world challenges while learning and taking responsibility.

Qualifications

• Currently enrolled in an advanced degree within a quantitative field such as physics, statistics, data science, or mathematical economics.
• Experience with data analysis and statistical modelling.
• Excellent problem‑solving skills and strong attention to detail.
• Ability to collaborate effectively in a fast‑paced team environment.
• No job too big, no job too small mindset, with a strong sense of urgency.
• Nice-to-have: Programming skills in Python, R, VBA, or similar.

Responsibilities

• Develop and improve trading algorithms for real-time asset optimisation.
• Build an understanding of the Physical Asset Management IT landscape and algorithmic decision engine.
• Analyse data and apply statistical models to support optimisation.
• Support the development, testing, and debugging of quantitative solutions.
• Contribute to the optimisation of renewables, batteries, and other asset classes.
• Collaborate closely with experienced colleagues across the team.

Skills

Data analysis

Statistical modelling

Problem solving

Attention to detail

Collaboration

Initiative

Learning mindset

Power trading experience

Education

Advanced degree in quantitative field (e.g., physics, statistics, data science, mathematical economics)

Tools

Python

R

VBA

Job description

Norlys Energy Trading A/S in Aalborg invites applications from motivated students to join the Physical Asset Management team. You will develop quantitative solutions to optimise energy assets in real time and support trading algorithms.

The role offers hands-on experience in a professional energy trading environment, collaboration with experienced colleagues, and a chance to apply academic knowledge to real-world challenges while learning and taking responsibility.