Data Engineer (Credit Data Science) (M/F)

Your next challenge:

  • Contribute to the development and maintaining of all the  modeling databases (Reference DataSet “RDS”) related to the credit risk quantification implemented by the Bank in the context of the implementation of minimum requirements regarding of the own funds calculation (Pillar 1 A-IRB approach);

  • Manage and ensure the consistency of the internal rating system integration within the risk management process and policies of the Bank as well as the data that is shared between several systems (Ongoing Model Monitoring).
  • Continuously follow up on new methods, technologies, market trends in Data Science (python and pandas versions, snowflake and dataiku…). Contribute to the “Lab” (or “R&D”) mindset of the team.

  • Transversal
    activities in collaboration with the IT team in order to manage and ensure the
    correct implementation of the IRB models.
  • Developing and maintaining the modeling databases for IRB modeling and backtesting purposes based on Oracle and/or SQL server databases .

  • Performing dedicated data quality during the development of the data flows, and ensure a complete and comprehensive documentation of the RDS (flows and data quality).

  • Collaborating with Internal Validation, Internal Audit and JST for the review and validation of the data flows and RDS.

  • Implementing the related recommendations and obligations if any.

  • Ensuring continuous improvement and necessary modifications in the data flows.

  • Ensuring training and knowledge transfer with the modeling team.

  • Redacting of business requirements for IT implementation as well as supporting the testing and the documentation of the implementation itself.

  • Technical
    support for the team
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