Job Description:
Qualification Needed:
- The successful candidate is expected to have a good working knowledge and delivery experience preferably within a Banking MI and Data Risk systems environment.
- Demonstrated ability to multi-task and work independently, as well as work collaboratively with other teams, some of which may be geographically distributed.
- Proven problem solving and analytical abilities including the ability to critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level information into details and apply sound business and technical domain knowledge.
- Sound knowledge of Relational and Non-Relational Database Platforms required.
- Experience in risk and control assessment across main relevant operational risk domains: information security and legal (data privacy)
- Experience with residual risks assessment based on a '16-box' framework incorporating guidance from experts across multiple domains would be advantageous
- Experience in various aspects of Data Quality Management including a full end to end data quality implementation will be advantageous
- Experience of process re-engineering and process management.
- Knowledge of data governance and management principles and processes.
- Knowledge of - Big Data- and Cloud Computing concepts
- Knowledge of BCBS239, IFRS-9 Stress Testing or experience of any other Banking regulatory environment is a big plus.
- Experience of building & implementing Data Quality solutions like DQ Tool via SAS / Python
- Experience of data mining & reporting in SAS
- Good to have knowledge of migrating SAS codes to Python
- Communicate openly and honestly.
. Advanced oral, written and visual communication and presentation skills - the ability to communicate efficiently at a global level is paramount.
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