The Intern – Data Analytics position at Siemens Gamesa Renewable Energy involves working within the Product Integrity (PPA) team of the Technology organization. The role focuses on developing and maintaining AI-powered tools that integrate data from multiple sources, create interactive dashboards (e.g., Power BI, Shiny), and automate reporting to support reliability-related decisions. Responsibilities include building and testing Python-based solutions, preparing data (cleaning, transformation, feature extraction), documenting workflows, and collaborating across cross-functional teams. The internship requires enrollment in a Master’s or final-year Bachelor’s program in Engineering, Data Science, Computer Science, or another relevant technical field, proficiency in Python and its data libraries, advanced English, and basic knowledge of machine learning concepts. The position is full-time and remote, offering opportunities to work with a global team, lead innovative projects, and benefit from flexible work arrangements.
Intern - Data Analyticis at Siemens Gamesa Renewable Energy
Remote - Spain, Navarra/Nafarroa, Sarriguren, Zaragoza, Aragon
Requirements
Education
- Master’s program in Engineering
- final-year Bachelor’s program in Engineering
- Bachelor’s program in Data Science
- Bachelor’s program in Computer Science
- Bachelor’s program in other relevant technical field
Experience
- Student (Not Yet Graduated)
Skills
- Python
- pandas
- NumPy
- data visualization
- Power BI
- Shiny
- machine learning concepts
- dashboards
- web-based interfaces
- automation
- data preparation
- cleaning
- feature extraction
Languages
- English (advanced)
Responsibilities
- Support the development and maintenance of AI-powered tools that integrate data from multiple sources, visualize insights through interactive applications 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.
Technologies
PythonpandasNumPyPower BIShiny
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