Intern in Algorithmic Trading & Asset Optimization (m/f/d)

Statkraft; Düsseldorf; Hybrid; EUR 10,000 - 17,000; Full time

Job summary

Statkraft invites an intern to join the Algorithmic Energy Management & Analysis team in Düsseldorf. You will engage in short-term analysis and trading, develop tools and models, and support day-to-day operations, applying time-series and statistical data analysis in a real energy market context.

The role emphasizes learning on the job, with collaboration across analysis and intraday trading units, and potential to focus on areas like algorithmic trading and automated asset optimization with

Qualifications

• Enrolled in a university degree, ideally in business, engineering, maths or science.
• Strong mathematical and statistical skills.
• Proficiency in programming (Python, Matlab or R preferred).
• Fluency in English to work in an international team (Düsseldorf & London).

Responsibilities

• Learn on the job through short-term analysis and trading activities.
• Develop tools and models; support operational activities.
• Work independently with guidance from various units (analysis, intraday trading).
• Contribute to development of models, benchmarking and monitoring processes.

Skills

Math

Python

Matlab

R

English fluency

Education

University student

Job description

Intern in Algorithmic Trading & Asset Optimization (m/f/d)

• Intern
• Business Units: ME - Energy Management

Statkraft has been making clean energy possible for over a century. That’s what we offer. 125 years of unrivalled expertise in supplying the world with what it needs most. We envision a world that runs entirely on renewable energy. Because in the fight against climate change, we don’t see renewable energy as part of the solution – we believe it must be the solution. With us, you’ll shape a career that is truly forward-facing with many amazing opportunities and offerings to match.

But there’s more work to be done – that’s why we need you to join us.

The energy sector is currently facing a strong transition towards digitalization and automation driven by decentralisation of (flexible) generation and increased market dynamics. To handle the resulting increased complexity efficiently, Statkraft makes use of algorithmic trading and virtual power plant solutions that automatically balance renewable generation, steer asset flexibility in real-time and run trading activities.

We are currently looking for an addition to our Algorithmic Energy Management & Analysis team located in Düsseldorf.

Learning on the job: You will engage in short-term analysis and trading, develop tools and models, and support operational activities. You will work independently while receiving support from various units, such as analysis and intraday trading, enhancing your fundamental knowledge of the energy markets.

Creativity and innovation: An important part is the new and further development of models, as well as benchmarking and monitoring processes, which are based on time series and statistical data analysis.

Contribute: Depending on your interests and skills, your internship will focus on the following areas:

• Algorithmic Trading: Studying of market data using statistical and machine learning methods. You contribute to the development of systematic and algorithmic trading strategies on the short-term power markets.
• Automated Flex & Asset Optimization: Development and analysis around the optimization of batteries, flexible generation and demand-side flexibility on short-term power markets and balancing markets in UK and continental Europe. You add value to the team by contributing to price forecasts, optimization algorithms and support day-to-day trading activities.

International working environment: You will be part of an English-speaking and highly international department, which is characterized by creativity, competence, willingness to innovate and a friendly, cooperative atmosphere.

Required Qualifications

• Enrolled in a university degree, ideally with a business, engineering, math or science background. We welcome applicants who do not yet have energy market experience.
• Solid mathematical and statistical skills
• Proficiency in programming (Python, Matlab or R preferred)
• Fluency in English to ensure optimal collaboration in an international team (Düsseldorf and London)

Nice to have – We’ll teach you otherwise

• Previous experience with machine learning, time series analysis, and statistical modelling is a plus
• Previous experience as intern/working student in energy, financial services or data science is an asset
• Proactive way of working

Duration: 6 Months, Expected start date: Earliest January 2027

Statkraft offers

• The chance to grow your career alongside a truly global network of experts, leaders, specialists and graduates from different countries and backgrounds
• A positive working environment characterised by competence, responsibility, and innovation and high focus on team achievement
• A diverse workplace regarding gender, age, and cultural background
• A focus on fun outside of work, supported by various activity groups such as soccer, yoga, sailing, climbing, boxing, cabin rentals, and much more
• Potential for long‑term collaboration as a working student after internship (up to 24 months in total) or cooperation in university thesis.

Our vision is to renew the way the world is powered. To navigate the complex journey ahead, we need every voice at the table. We therefore work actively to be a diverse and inclusive workplace and welcome all applicants regardless of background, gender, age, sexual orientation, religious belief, ethnicity, nationality or disability.

Statkraft offers competitive terms of employment and benefits schemes, and we’re a trusted employer that puts the safety of our people first. We believe that a safe and healthy working environment is a matter of choice, not chance.

Statkraft manages critical infrastructure and services in several countries.We conduct background checks on qualified applicants before hire.The applicant must be eligible for security clearance andauthorisation.