As a responsible bank, the issue of security and trust is of the utmost importance to us. So that we can continue to detect anomalies and fraudulent patterns and prevent fraud, we are looking for an experienced developer to join our DevOps team “Fraud Hunter”. The agile teams are self-organized and accompany the applications throughout the entire product life cycle. Are you an experienced developer and already have initial experience in developing and evaluating data analysis tools? Do you love a challenging mix of self-developed applications and the integration of products in the field of artificial intelligence?
Is your appetite to help shape our perimeter as a data scientist in the future? Are you interested in using complex algorithms to determine cause-effect relationships and create quantitative forecast models? Then you are exactly right with us!
- New and further development of our fraud detection system in sophisticated combination with electronic customer channels
- Technical conception, analysis and design of features to improve fraud detection
- Conception, development and implementation of advanced machine learning algorithms and AI models in close collaboration with suppliers
- Introducing new technical and methodological impulses to take the current setup even further
- Responsible for training, evaluation and optimization of the models
- Ethics are important to you and you are interested in security and fraud prevention
- You have a sound education in the areas of computer science and/or mathematics
- You have several years of experience in agile software development and DevOps
- You have initial experience in designing data architectures
- You have good communication skills in German and English
- Good knowledge of Python
- several years of experience with machine learning, model training, data analysis and evaluations
- Experience with development tools (including Git, Intellij, Matplotlib, Sklearn, Pandas, PySpark)
- Good SQL database knowledge
- Experience with Linux
- Experience with Elasticsearch is an advantage
We use a “state of the art” TechStack:
- We further develop data preprocessing/trianing pipelines & train new
models using Pandas, Sklearn, Spark, etc.
- Development tools: Git, Pycharm, PySpark, Matplotlib, Sklearn, Pandas, Multliputty