The monitoring & screening tribe is responsible for detection and prevention of financial crime: Fraud, Money Laundering and Sanctions breaches. We do that by applying models to all transactions passing through the bank and detecting outliers that warrant further investigation, supporting the investigation with data from internal and external sources to support fast and accurate decision making and following through until the case is closed.
We are expanding our analytical capability to extend beyond simple rule based detection to machine learning across all our areas of responsibility. To support the data scientists in this area we are building up our capability across Data Engineering and Machine Learning Operations. Data Engineering is responsible for building the data pipelines while pushing the boundaries of the newest available technologies. We strive for building robust, scalable and easy maintainable solutions, the bank is now starting the journey to move to the Public Cloud.
You main responsibility will be to build the data pipelines for the analytical models. The pipelines will be built by utilizing both internal and external data in both our Data Warehouse and our Hadoop Cluster. All tasks will be solved as part of multifunctional squad consisting of Data engineers, Machine Learning operations as well as experts in the AML field.