About the role

Senior Manager providing insider risk detection oversight for a leading financial institution. Ensures rigorous monitoring and challenge of detection capabilities across IT, cybersecurity, and HR controls.

Responsibilities

As a member of the Bank's second line of defense, the Senior Manager, Insider Risk Detection Strategy & Modeling Oversight provides oversight, monitoring, and challenge of the insider risk detection capabilities taking into consideration an understanding of IT, cybersecurity, and HR controls.
This role delivers credible challenge on rules, models, processes, analytics, and other advanced tools.
This role provides oversight, monitoring and credible challenge to first line insider risk analytics & detection strategies, rules, models, and change activity.
This position performs and oversees risk reviews and credible challenge of insider risk detection models such as user behavior analytics (UBA/UEBA), anomaly detection, and entitlement analytics.
It also challenges the design and operation of rule logic, including toxic combinations, exception thresholds, and dual-control triggers.
This is a highly technical role that provides oversight, monitoring and challenge on the orchestration, architecture, data governance, and workflow development supporting insider risk detection.
The Senior Manager evaluates how monitoring tools and platforms, including SIEM/UBA solutions, data loss prevention systems, and workflow/case management applications, are designed, integrated, and optimized, ensuring both technical efficacy and control sustainability.

Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science)
Graduate's degree preferred with either progressive project work experience, or; 7+ year of relevant experience; higher degree education and research tenure can be counted
Master's degree or relevant professional certifications (e.g., CFE, CISM, CISSP, CRISC, or equivalent) strongly preferred
Experience in fraud risk management, insider threat, cybersecurity, internal audit, or investigations within financial services; demonstrated expertise in overseeing internal-fraud / insider threat detection strategies and analytics strongly preferred
Deep knowledge of internal-fraud typologies and controls, including privileged access, toxic combinations, segregation of duties, dual controls, and exception monitoring, along with proficiency in monitoring technologies such as UBA/UEBA, DLP, SIEM, and workflow analytics
Proven ability to design and oversee internal-fraud detection rules and models, including performance monitoring, back-testing, and change governance; familiarity with AI/ML applications and related governance expectations.