Surveillance Tuning Expert

Alert Optimization & Tuning Evaluate existing surveillance models and alert parameters to identify opportunities for performance improvement. Conduct systematic tuning exercises to reduce false positives and ensure optimal detection of true risk events. Apply data-driven methodologies and quantitative analysis to assess rule thresholds, data feeds, and scenario logic. Model Performance Analysis Develop metrics and dashboards to monitor surveillance model performance, precision, recall, and false positive ratios. Conduct back-testing, sample reviews, and trend analysis to validate rule effectiveness. Collaborate with global compliance teams to support model enhancements or machine learning implementations. Data Quality & Governance Partner with technology teams to identify and resolve data integrity issues impacting alert quality. Review source systems and feeds to ensure complete and accurate capture of trading data. Stakeholder Collaboration Work closely with global Compliance Officers teams to define model requirements and tuning objectives. Document tuning methodologies, assumptions, and validation outcomes in accordance with regulatory and audit expectations.