of experience in data analytics, risk analysis, or statistical modelling within financial services or a regulated environment.
Minimum
3 years
of hands-on experience in Compliance Data Science, including developing and validating compliance models, working with large datasets, and implementing advanced analytics solutions in major banking institutions.
Proven expertise in leveraging
data science methodologies
(e.g., machine learning, predictive modelling) for financial crime risk management.
Strong understanding of
compliance frameworks
, regulatory requirements, and financial crime typologies (AML, sanctions, TBML).
Experience with
data visualization tools
(e.g., Power BI, SAS Visual Analytics) and programming languages such as SAS, Python, R, or SQL.
Familiarity with compliance technology platforms and system architecture for transaction monitoring and sanctions screening.
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