A strong graduate/postgraduate degree in a quantitative discipline (e.g., Engineering, Statistics, Computer Science, Mathematics) or equivalent experience
Experience with natural language processing and unstructured data analysis
Experience with Machine Learning and Artificially Intelligence ideally with Large Language Models and/or pattern recognition techniques
Strong development skills, particularly in languages commonly used in compliance analytics (Python, R, SQL)
Strong verbal and written communication skills, especially in explaining technical concepts to non-technical stakeholders
Self-motivated work attitude with ability to work independently
Experience in model validation or similar quality assurance roles
Desirable:
Established experience in compliance monitoring systems and models, particularly in AML and Market Surveillance domains
Strong understanding of financial crime typologies and regulatory requirements
Familiarity with major AML/Surveillance platforms (e.g., NICE Actimize, Nasdaq SMARTS)
Knowledge of relevant regulations (e.g., MiFID II, MAR, BSA/AML requirements)
Professional certifications in AML or Compliance (CAMS, FRM, etc.)
Experience working with regulatory bodies or handling regulatory examinations
