What to expect:
- Conceptualization and implementation of data science projects
- Integration of new data sources and implementation of data preprocessing
- Conducting statistical data analyses and data visualizations
- Development of algorithms, for example, for pattern/anomaly detection
- Utilizing LLMs for innovative solution creation for various problems, including the application of prompt engineering, output validation, and evaluation of results
- Designing and developing software solutions to apply these tasks
- Optimization, automation, and further development of existing applications
- Advising internal and external colleagues in customer projects
- Collaboration in interdisciplinary teams consisting of, for example, data scientists & engineers, system engineers, project managers
What you bring along:
- Studies in data science, computer science, mathematics, natural sciences, or comparable fields of study or relevant professional training
- Excellent knowledge of Python and agile development of software and algorithms
- Good knowledge in the field of machine learning (i.e. scikit-learn, Tensorflow, PyTorch) is required
- Good knowledge of statistics is an advantage
- Experience with LLMs and prompt engineering is an advantage
- Proficiency in cloud and edge technologies, databases, and data processing methods
- Strong communication and persuasion skills at both the operational level and in coordination with management
- High proactivity and self-responsibility
- Fluent English skills