Siemens Energy

• Conducting literature review on multi-source data integration in time series forecasting
• Collecting and preprocessing diverse data types including text, financial, and sensor data
• Developing and implementing machine learning models for integrating multiple data sources
• Evaluating the impact of multi-source data integration on forecasting accuracy
• Documenting research processes and results comprehensively
• Presenting research findings to the team and partner
  
  

• Master’s enrollment in Data Science, Computer Science, Statistics, or related fields
• Experience with time series analysis and machine learning techniques
• Proficiency in programming languages such as Python or R (preferably R)
• Familiarity with natural language processing (NLP) and sentiment analysis methods
• Strong analytical skills for data interpretation and model evaluation
• Effective communication skills for documentation and presentation of research findings

At Siemens Energy, we are more than just an energy technology company. With ~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.      

• Exciting insights into an international company
• Lay the foundation for your career with us