Intern - Data Analytics
About the Role
Location Spain Navarra/Nafarroa Sarriguren
1. Country: Spain
2. State/Province/County: Aragon
3. City: Zaragoza
Company Siemens Gamesa Renewable Energy Innovation & Technology, Organization Wind Power Business Unit Technology Full / Part time Full-time Experience Level Student (Not Yet Graduated)
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
4. Support the development and maintenance of AI-powered tools that integrate data from multiple sources, visualize insights through interactive applications (, Power BI, Shiny), and automate presentation generation to supervise reliability-related changes and decisions.
5. Use Python and relevant libraries to build, test, and improve these tools, focusing on usability, automation, and value to engineering teams.
6. Assist in data preparation tasks, including cleaning, transformation, and feature extraction, to ensure data is structured and ready for analysis and visualization.
7. Document workflows, design choices, and outputs to ensure clarity, reproducibility, and effective knowledge sharing across partners.
8. Collaborate with experts across data analytics and digitalization functions within and beyond the Design for Reliability (DfR) program.
What You Bring
9. Enrollment in a Master’s or final-year Bachelor’s program in Engineering, Data Science, Computer Science, or another relevant technical field.
10. Knowledge in Python, with a focus on building data-driven tools or applications. Familiarity with common Python libraries for data handling, analysis, or automation (, pandas, NumPy, or equivalent).
11. Advanced english is a must
12. Basic understanding of machine learning concepts and their application in real-world tools (, classification, clustering, anomaly detection).
13. Curiosity about developing dashboards or web-based interfaces (, Power BI, Shiny, or lightweight web apps).