Data Scientist - AML & Compliance Analytics (Ciudad de México, Cuauhtémoc)
Core
Design advanced monitoring models and algorithms to detect money laundering typologies, identify anomalies, and analyze network structures to safeguard financial integrity.
Role type
Senior Data Scientist (AML & Compliance Analytics)
Builds
Production ML models, data pipelines, and risk segmentation tools for anti-money laundering and compliance.
Domain
Financial Services / Anti-Money Laundering (AML) / Compliance
Deliverable
production ML models
Required skills
Python, PySpark, SQL, Clustering algorithms (K-means, DBSCAN), Supervised classification models, Network Analysis (Graph Analysis), Large-scale database management
Preferred skills
Distributed architectures, Graph libraries (NetworkX, PyG, Neo4j), CAMS certification, Intermediate-advanced English
Technologies
Python, PySpark, SQL, Gradient Boosting, Neural Networks, NetworkX, Neo4j
Responsibilities
Design advanced monitoring models for money laundering detection in batch and real-time; Implement ML algorithms for anomaly identification; Execute network analysis to identify shell companies and beneficial owners; Build and optimize data pipelines using PySpark; Design customer risk segmentation models (KYC/KYB); Validate and calibrate alert thresholds; Ensure regulatory compliance with financial authorities; Present technical findings to the Communication and Control Committee; Mentor junior team members in AML/PLD.
Seniority
Senior, hands-on IC with mentorship responsibilities
