• Designing and setting up a modular and future-proof machine learning framework. Possible tasks:
• Implementing best practices for data preprocessing, model training, validation, and deployment.
• Integrating maintenance and feedback principles within the context of machine learning: such as monitoring model performance and retraining models.
• Version management.
• Visualizing and sharing results. Providing system logging.
• Preparing the infrastructure for migration to cloud environments.
• Documenting processes.
• Coaching team members in the use of the framework.

• Presenting the analysis to business services.

• Developing and applying machine learning models. Possible tasks:

• Translating business questions into technical solutions in short iterations.
• Identification and verification of data sources.
• Data analysis.
• Data preparation.
• Feature engineering to create meaningful variables.
• Exploratory data analysis to uncover data patterns, assess data quality, and optimize model input.
• Selection of algorithms.
• Developing, comparing, and tuning predictive models.
• Automation of the process.
• Visualizing and presenting results in an understandable and convincing manner.
• Continuously evaluating and optimizing the models.

The consultant must be able to communicate fluently in the other national languages.

The interview will be combined with a practical assignment.

Technical skills:

• Knowledge of analytical models.
• Machine learning techniques