Siemens Energy

• Apply statistical and machine learning techniques to energy and industrial data to create predictive and prescriptive models. 
• Design reusable data science components for preprocessing, feature engineering, and statistical evaluation. 
• Collaborate with MLOps engineers to operationalize models in robust, scalable ML pipelines. 
• Contribute to experimentation workflows, model explainability, uncertainty quantification, and fairness evaluation. 
• Support automatic model selection, tuning, and lifecycle monitoring across environments (cloud, on-prem, edge). 
• Collaborate with multi-functional teams to translate business and engineering requirements into data-driven solutions. 

• Master’s degree in Data Science, Computer Science, Applied Mathematics, or a related technical field
• Extensive experience applying classical data science and statistical modeling to real-world challenges
• Proficient in Python with hands-on expertise in pandas, scikit-learn, and NumPy
• Skilled in ML/AI frameworks (e.g., PyTorch, TensorFlow) with experience in experimentation and model evaluation
• Knowledge of MLOps practices and tools such as MLflow, Airflow, or Kubeflow (preferred)
• Bonus: Familiarity with LLMs, Generative AI architectures, or deploying models to edge environments

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.      

• In addition to an attractive remuneration package in line with the market, you can expect an attractive employer-financed company pension scheme
• We also offer the opportunity to become a Siemens Energy shareholder
• We offer our employees the opportunity to work flexibly and remotely, and our inspiring offices provide space for collaboration and creativity
• The professional and personal development of our employees is very important to us. We provide them with the opportunities to learn and develop in a self-determined way, various attractive programs and learning materials are available for this purpose
• In relation to the "compatibility of family and work", we have a wide range of offers, e.g. flexible working time models, childcare places at many locations, the possibility of trial part-time work or even a sabbatical