
Technical Advisor - Synthetic Data for Compliance Testing (m/f/d)
- Riyadh
- Contract
- Full-time
- Design and generate AI-driven synthetic financial datasets that accurately replicate real-world transactional behaviors, enabling realistic compliance stress testing.
- Embed structured AML typologies, financial crime red flags, and sophisticated money laundering patterns into synthetic transaction flows.
- Apply adversarial machine learning (AML-ML) to stress-test existing compliance detection algorithms, identifying blind spots and weak signals.
- Establish quantitative benchmarks for AML detection performance, measuring false positive/negative rates, detection lag, and operational efficiency.
- Develop scoring mechanisms for compliance system resilience, testing institutions' ability to detect and react to synthetic AML threats.
- Conduct controlled regulatory stress tests to assess how well compliance teams and automated systems handle high-risk financial crime scenarios.
- Central Banking
- Technology Sector