Siemens Energy

A Snapshot of Your Day

Are you passionate about AI, data visualization, and giving to the green energy transition? Join our Product Integrity (PPA) team within Siemens Gamesa’s Technology organization. In this role, you will help develop and maintain intelligent tools that support Design for Reliability (DfR) initiatives across our wind turbine platforms. You will supply to the creation of AI-driven solutions that capture and connect data from multiple sources, power interactive dashboards, and automate reporting to support data-driven decisions. Working closely with engineers, data scientists, and other cross-functional experts, you will play a significant role in improving the way our team analyzes and communicates reliability performance.

How You’ll Make an Impact

• Support the development and maintenance of AI-powered tools that integrate data from multiple sources, visualize insights through interactive applications (e.g., Power BI, Shiny), and automate presentation generation to supervise reliability-related changes and decisions.
• Use Python and relevant libraries to build, test, and improve these tools, focusing on usability, automation, and value to engineering teams.
• Assist in data preparation tasks, including cleaning, transformation, and feature extraction, to ensure data is structured and ready for analysis and visualization.
• Document workflows, design choices, and outputs to ensure clarity, reproducibility, and effective knowledge sharing across partners.
• Collaborate with experts across data analytics and digitalization functions within and beyond the Design for Reliability (DfR) program.

What You Bring

• Enrollment in a Master’s or final-year Bachelor’s program in Engineering, Data Science, Computer Science, or another relevant technical field.
• Knowledge in Python, with a focus on building data-driven tools or applications. Familiarity with common Python libraries for data handling, analysis, or automation (e.g., pandas, NumPy, or equivalent).
• Advanced english is a must
• Basic understanding of machine learning concepts and their application in real-world tools (e.g., classification, clustering, anomaly detection).
• Curiosity about developing dashboards or web-based interfaces (e.g., Power BI, Shiny, or lightweight web apps).

About the Team

The SE WP TE PI PPA team is part of Siemens Gamesa’s Technology organization and plays a relevant role in improving the reliability and performance of our wind turbine platforms. We work multi-functionally on problem-solving, root cause analysis, and digital innovation initiatives, all passionate about improving turbine integrity and lifecycle performance.

Who is Siemens Gamesa?

Siemens Gamesa is part of Siemens Energy, a global leader in energy technology with a rich legacy of innovation spanning over 150 years. Together, we are committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. As a leading player in the wind industry and manufacturer of wind turbines, we are passionate about driving the energy transition and providing innovative solutions that meet the growing energy demand of the global community.

At Siemens Gamesa, we are constantly seeking talented individuals to join our team and support our focus on energy transformation.

Find out how you can make a difference at Siemens Gamesa: https://www.siemensenergy.com/global/en/home/careers/working-with-us.html

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

Here are examples of the rewards and benefits Siemens Energy offers:

• Opportunities to work with a global team
• Opportunities to work on and lead a variety of innovative projects
• Remote/Flexible work
• Help with food
• Continual learning