About the Role
Job ID
295153

Location

Denmark

Midtjylland

Brande

Company
Siemens Gamesa Renewable Energy A/S

Organization
Wind Power

Business Unit
Offshore

Full / Part time
Part-time

Experience Level
Entry-Level / Graduate

A Snapshot of Your Day
As a Student Worker within Data Science/Engineering, your day will involve applying your machine learning skills to big data sets, contributing to innovative projects in the field of wind turbines. You will engage in various tasks, from developing machine learning models from scratch to performing data analysis. This role will provide you with hands-on experience in a dynamic environment, where you will enhance your technical skills and contribute to the advancement of Siemens Energy’s initiatives.

The position is part-time, requiring 1 day a week in the office (Brande), with a hybrid work model that accommodates your schedule

We are only looking for students currently at their last year at the bachelor's degree or enrolled in a Master’s degree with a minimum of 1,5 year left, preferably within Data Science, Statistics, Mathematics, or Computer Science.

How You’ll Make an Impact

Model Development & Improvement

• Develop machine learning models from scratch and improve existing models.

• Apply models to new data sets and conduct data analysis.

• Scope projects and goals, ensuring alignment with innovative research in machine learning.

• Visualize data for user consumption, potentially utilizing Power BI.

• Present data insights.

• Work independently while collaborating with team members in an agile environment.

What You Bring

• Currently at your last year at your Bachelor degree or enrolled in a Master’s degree with a minimum of 1,5 year left, preferably in Data Science, Statistics, Mathematics, or Computer Science.

• Strong theoretical foundations in machine learning, with a preference for computer vision.

• Comprehensive skills in Python and machine learning libraries, along with fluency in SQL.

• Familiarity with classic software development concepts like Git, servers, GPUs, and cloud services.

• A keen interest in processes and documentation, with strong organizational skills.

About the Team
Join a team that values accuracy, collaboration, and continuous improvement. You will have the opportunity to develop your professional skills in a global environment. We offer flexible working hours that support your studies and an inclusive team culture where knowledge-sharing and professional development are at the core. Become part of a company committed to enabling the energy transition and shaping a sustainable future.

Who is Siemens Energy?
At Siemens Energy, we are more than just an energy technology company. With approximately 100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one-sixth of the world’s electricity generation.

Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation. Find out how you can make a difference at Siemens Energy: Employee Video

Our Commitment to Diversity
Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion, and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character—no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.

Rewards/Benefits

• Flexible working hours to accommodate your study schedule.

• An encouraging and collaborative work environment with opportunities for growth and development.

• Hands-on experience in data science and engineering support.

Application
Don’t hesitate to apply before August 4th 2026. Ongoing selection is applied; the role might be filled before the last application date.

Location: 7330 Brande, DK

Please contact TA Partner, Simone Præsius if you have any questions regarding the recruitment process: [email protected]