Intern – Energy Market Modelling and Analytics

DNV’s Energy Markets Analytics Southern Europe team is offering an internship for a motivated student or recent graduate in Electrical Engineering, Energy Engineering, or a related quantitative discipline. The successful candidate will support the team’s energy market analysis and energy system modelling activities.

Key responsibilities include:

• Supporting the development of advanced energy market models to forecast electricity prices, assess market trends, and optimize energy assets.
• Contributing to data analysis, scenario development, model validation, and the continuous improvement of analytical tools and workflows, including data processing and model automation.

At DNV, you will gain hands-on experience in a global company where you can learn from industry experts, work on meaningful projects, and develop your professional skills. As an intern, you will be part of an international and collaborative team, supported by colleagues who are passionate about sharing knowledge and helping you grow. You will have the opportunity to contribute from day one while gaining valuable insight into your chosen field and building a strong foundation for your future career.

DNV is an Equal Oppertunity Employer and gives consideration for employment to qualified applicants without regard to gender, religion, race, national or ethnic origin, cultural background, social group, disability, sexual orientation, gender identity, marital status, age or political opinion. Diversity is fundamental to our culture and we invite you to be part of this diversity.

• Currently pursuing, or recently completed, a degree in Electrical Engineering, Energy Engineering, or a related quantitative discipline.
• Interest in energy markets, renewable energy, battery energy storage, and the broader energy transition. Previous industry experience is an advantage but is not required.
• Familiarity with energy system modelling tools such as PLEXOS or PyPSA; mathematical optimization tools such as Pyomo; machine learning libraries such as Pandas, NumPy, SciPy, or Scikit-learn is an advantage.
• Strong analytical and problem-solving skills, with programming experience in Python and SQL. Familiarity with software engineering practices such as Git, documentation, and collaborative development workflows is a plus.
• Proficiency in English; knowledge of Italian is an advantage.
• Curious, proactive, collaborative, and eager to learn.