E.ON Digital Technology GmbH | Permanent | Part or Full Time

Take this opportunity to join the Technology Consulting division at E.ON’s Digital Technology organization. Our division is a key internal professional services entity that spearheads the delivery of E.ON’s Digital Transformation Strategy. E.ON, a top European utility company, is instrumental in the energy transition, connecting everyone to sustainable energy.

If you are passionate about technology and committed to making the world greener, join our dynamic and diverse team as a changemaker (f/m/d).

About the Role

Do you have a passion for data and technology? Do you believe in the importance of sustainability? Are you ready to drive the green energy transition forward? This position is crafted for you. Your expertise will help shape the future.

We recognize the immense responsibility we hold for our customers, assets, and the environment. Our focus is on analyzing and developing solutions using advanced data and machine learning technologies to enhance service quality, efficiency, and overall smartness.

Responsibilities

• Collaborate with data scientists, data engineers, business, and infrastructure experts to design and develop scalable data/AI-based solutions with a global impact within E.ON.
• Stay updated with industry trends and emerging technologies in data science, architecture, and engineering.
• Evaluate new data technologies to integrate cutting-edge machine learning solutions and analytical modules into operational cloud services efficiently.
• Improve efficiency and time-to-market by implementing reusable artificial intelligence models and data-driven solutions.
• Enhance analytics capabilities by extracting information from diverse data sets, including structured, unstructured, batch, and streaming data.
• Ensure high quality and stability through agile processes and peer code reviews.
• Share innovative ideas and propose new pathways.

Qualifications

• At least 3 years of professional experience in a data scientist or data engineering role.
• A degree or PhD in Computer Science or a related technical field.
• Experience in coding to ingest and process large, diverse data sets; perform time series and statistical data analysis; develop optimization algorithms; and build supervised and unsupervised models, primarily in Python. Proficiency in additional programming languages is a plus.
• A strong affinity for mathematics and statistics.
• A passion for science and problem-solving through data, combined with a strong drive to deliver valuable business solutions.
• Knowledge of Machine Learning frameworks such as scikit-learn, TensorFlow, PyTorch, and Azure ML, including ML interpretability.
• Experience with data transformations in Spark and Databricks is a plus.
• Proficiency in implementing end-to-end pipelines to ingest data and deploy, monitor, and maintain analytical/ML/AI modules in cloud environments like Azure, AWS, or GCP.
• Familiarity with git and CI/CD workflows; knowledge of Azure DevOps is an additional advantage.
• Excellent writing and communication skills, with the ability to adapt your style to your audience.
• Comfortable collaborating internationally and across cultural borders.
• Fluent in English; German language skills are an advantage.
• Extensive knowledge of the energy industry is a plus.
• Experience with visualization tools like Tableau or Power BI is beneficial.
• Background in Consulting is advantageous.

What to Expect at E.ON Digital Technology

We offer a unique opportunity to combine your passion for technology with your commitment to societal relevance. Contribute to E.ON’s ambitious digitalization strategy, broaden your expertise through varied assignments, work with cutting-edge technology, and grow your career internationally within the wider organization.

Have Questions?

For further information, please contact Sarah Klammer at .

Additional Information

Job Req ID: 227939
Contract Type: Permanent
Working Time: Part or Full Time
Company: E.ON Digital Technology GmbH
Locations: Berlin, Hannover, Würzburg, München, Hamburg, Frankfurt am Main, Essen, Potsdam
Function Area: