Development and optimization of algorithms to detect anomalies in portfolio level behavior.
Analysis of the emerging threats, in collaboration with Strategy and Policy partners, and expansion/refinement of the monitoring for known high risk behaviors.
Design and implementation of visual dashboards supporting anomaly detection alerting process
Assist with the deployments of the monitoring algorithms in coordination with various Tech partners.
Work with Data Science team on development of the advanced anomaly detection techniques, including unsupervised machine learning.
Initial triage of the monitoring alerts to understand the drivers behind the anomalous behavior.
Hands on experience in SAS, PySpark and Hive
Strong SQL skills with commensurate experience in a large database platform
A strong willingness to learn new technologies and ability to think critically.
Robotic process automation to reduce the need for manual, repeatable processes
