Student Quant Analyst - Real-Time Energy Optimisation

Norlys Energy Trading; Aalborg; On-site; DKK 83,000 - 124,000; Part time

Job summary

Norlys Energy Trading in Aalborg, Denmark, invites a student to join the Physical Asset Management team. You will help develop quantitative solutions that optimise energy assets in real time and support trading algorithms across renewables and batteries.

As a student, you will gain hands-on experience, work 15 hours per week, and collaborate with experienced colleagues in a fast-paced environment where theory becomes practice and continuous learning is encouraged.

Qualifications

• Currently enrolled in an advanced degree within a quantitative field.
• 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.
• A proactive, can-do mindset and urgency.

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

Quantitative thinking

Data analysis

Statistical modelling

Problem solving

Attention to detail

Team collaboration

Initiative

Education

Advanced degree in physics/statistics/data science/economics

Tools

Python

R

VBA

Job description

Norlys Energy Trading in Aalborg, Denmark, invites a student to join the Physical Asset Management team. You will help develop quantitative solutions that optimise energy assets in real time and support trading algorithms across renewables and batteries.

As a student, you will gain hands-on experience, work 15 hours per week, and collaborate with experienced colleagues in a fast-paced environment where theory becomes practice and continuous learning is encouraged.