Responsibilities:

- Actively monitor and identify data disparities and suspicious activity early. 
- Detect money laundering activities and prevent the adverse effects they create, including disciplinary action, substantial fines, and damage to a company’s reputation. 
- File suspicious activity report by data from transaction history, KYC, CIP (customer identification program), PEP (politically exposed person), and AML (anti-money laundering). 
- Use AI-calculated credit rating to achieve customer segmentation and rank-ordering of AML alarms.

Essential Requirements:
- Takes initiative to identify & report problems and to drive resolution
- Results oriented and has a high degree of accountability, commitment and responsibility
- Extensive programming experience in Python
- Experience with data-driven statistical or machine learning methods
- Strong preference for hands-on experience with TensorFlow or similar frameworks
- Experience in querying complex schemas and relational databases

Desirable Qualifications:
- Master or PhD degree in computer science, data science or any related field or equivalent practical experience
- Any practical experience in financial markets, particularly relating to High Frequency Trading systems
- Any related experience in AML detection and prediction
- Extensive programming experience, particularly in Go or R
- Familiar with SQL and NoSQL databases
- Familiar with Linux, AWS/GCP