Student Quantitative Analyst

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

Are you passionate about quantitative analysis, technology, and energy markets?

Join our Physical Asset Management team and help develop quantitative solutions that optimise energy assets in real time. You'll work alongside experienced colleagues in a fast-paced environment where you'll quickly turn theory into practice and gain hands‑on experience within energy trading.

About the team

We are a team of experienced specialists working with the optimisation of energy assets. We set high standards, collaborate closely, and believe the best results come from curiosity, knowledge sharing, and continuous development.

About the role

You'll contribute to the development of quantitative solutions used to optimise energy assets in real time. You'll gain insight into our technical landscape while supporting the development, testing, and improvement of trading algorithms that create value across our portfolio of assets, including renewables and batteries.

Your key responsibilities

You'll support the team across a range of quantitative and technical tasks, contributing to the continuous development of our optimisation capabilities. Your responsibilities will include:

• 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.

This role offers a unique opportunity to combine quantitative analysis, technology, and energy markets. You'll work on solutions that create real value while gaining hands‑on experience in a collaborative team where learning and continuous development are part of everyday work.

Head of Intraday Analytics

What we are looking for

We're looking for a curious and motivated student who enjoys combining quantitative thinking with technology and problem-solving. You take initiative, enjoy collaborating with others, and are eager to learn.

Must-have

• 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.
• A "no job too big, no job too small" mindset, a can‑do attitude, and a strong sense of urgency.

Nice-to-have

• Programming skills in Python, R, VBA, or similar languages.
• Experience within power trading.

What we offer

You'll join an experienced team where you'll have the opportunity to apply your academic knowledge to real-world challenges while developing your technical and analytical skills.

• Hands‑on experience in a professional energy trading environment.
• Close collaboration with experienced colleagues in Physical Asset Management.
• A steep learning curve and high level of responsibility.
• A student position of 15 hours per week, allowing you to combine work with your studies.