Job Description

Your job

  • Research state‑of‑the‑art data science and NLP methods to identify entities hidden within payment data.
  • Develop AI and machine learning models - especially transformer‑based models at the character level - to extract entity information from financial transactions.
  • Investigate the suitability and performance of transformer architectures for entity extraction in the context of counterparty identification.
  • Design and implement methods to monitor the correctness, robustness, and ongoing quality of the developed models.
  • Work with Python and PySpark in Databricks to build, train, and evaluate data science solutions.
  • Transform your prototypes into internal data science products that can be used operationally within the Detecting Financial Crime (DFC) domain.
  • Report your ideas, research findings, and progress through written documentation and presentations to ensure knowledge sharing and structured feedback, as we...
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