We are shaping the future of energy through intelligent charging and energy solutions for electric mobility. As part of the Volkswagen Group, we are building one of the first fully integrated charging and energy platforms for drivers and fleet managers of electric vehicles. Our mission is to make energy usage simple, smart, and efficient — and to actively contribute to the energy transition.
To support our growing power trading activities, we are looking for a Working Student / Intern in Energy Trading who is eager to gain hands-on experience in energy markets, quantitative analysis, and trading operations. You will work closely with experienced traders and analysts and gain deep insights into how data, models, and market dynamics come together in a real trading environment.
If you are curious about energy markets, enjoy working with data and code, and want to help shape the future of electricity trading, we’d love to hear from you.
Possible Tasks within this Role
- Work closely with the power trading team and contribute to ongoing initiatives and projects.
- Support daily operational processes, gaining first-hand insight into market dynamics, data flows, and decision-making in a trading environment.
- Assist with the development, testing, and maintenance of analytical tools and quantitative models used by the team.
- Perform market research and data-driven analyses to support trading strategies, risk assessment, and operational improvements.
- Provide general operational and analytical support to the team as needed, ensuring accuracy and reliability of data and outputs.
- Continuously learn about power markets, products, and trading workflows, and proactively suggest improvements where possible.
Qualification requirements
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Currently enrolled in a Bachelor’s or Master’s program in Mathematics, Computer Science, Engineering, Statistics, Economics, or a related quantitative field. CQF candidates or alumni highly welcome.
- Solid programming skills in Python and SQL; experience with additional languages or tools (e.g. Git, DevOps, CI/CD, etc.) is a plus.
- Strong analytical mindset with the ability to structure problems and derive insights from data.
- High attention to detail and confidence working with large, complex datasets.
- Good communication skills and the ability to collaborate effectively in a team-oriented environment.
- Experience with machine learning and time-series data analysis is highly desirable.
- Prior exposure to energy markets, trading, or quantitative finance (e.g. through coursework, internships, or projects) is a strong advantage.