Data Scientist / MLOps Engineer (f/m/d)

permanent
Start: As soon as possible
Job-ID: 9775

In this role, I lead the advancement of AI and MLOps across the entire organization.

What makes this job interesting for me: 50Hertz has been committed to the energy transition for a long time. The Data Science team is directly driving the digital transformation within the company. In my role, I am responsible for the development and secure operation of AI-based solutions. In this environment, I have the opportunity to continuously enhance my expertise through collaboration with specialists.

My Responsibilities:

• Development and Maintenance: Writing clean, efficient, and scalable Python code for machine learning applications,
• Service Management: Monitoring and maintaining ML models in production environments, including on-call duties (24/7),
• Data Processing: Preparing, cleaning, and transforming data to ensure high-quality datasets,
• Integration and Deployment: Optimizing ML workflows for deployment in production environments,
• Collaboration: Working with Data Scientists, ML Engineers, and Data Engineers to implement solutions,
• Documentation: Maintaining comprehensive documentation of codes, processes, and models,
• Actively Engage in Data Chapter: Sharing results within Chapters, Product Clusters, and possibly conferences; coordinating interfaces and standards within the Elia Group,
• Ambassador for AI and MLOps: Staying updated on AI and Advanced Analytics techniques.

My Competences:

• Experience: 5+ years in a related role in Data Science/Engineering,
• Programming Skills: Strong knowledge of Python and its libraries/frameworks (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Flask/FastAPI),
• Machine Learning Expertise: Practical experience with ML algorithms, data preprocessing, feature engineering, and model evaluation,
• Operational Skills: Knowledge of monitoring tools for ML services (Prometheus, Grafana),
• Problem Solving: Strong debugging and troubleshooting skills,
• Data Processing: Experience with large datasets and databases (SQL, MongoDB),
• Version Control: Familiarity with Git and collaborative development workflows,
• Cloud Platforms: Experience with cloud services (AWS SageMaker, Google Cloud AI, Azure ML),
• Communication Skills: Ability to explain technical concepts to both technical and non-technical stakeholders.

Additional Preferences:

• Understanding of Kafka,
• Experience with MLFlow,
• Experience with AzureML.
  

Flexi Compass - see how flexible this vacancy is

• Working hours per week: 37 hours (full time),
• Flexible working hours and a long-term working time account supporting your work-life-balance,
• The number of flex days is not limited,
• No core working hours,
• Mobile working, also from home, is possible.