Lead Analyst — AI Operations Support

This role involves leading the AI Operations support function for a critical risk technology team. You will be responsible for the end-to-end production monitoring, performance oversight, and automation of AI-enabled controls within complex risk-reporting pipelines. This is a hybrid position focused on ensuring the stability and accuracy of AI-driven financial risk processes.

Our client is a leading global provider of financial services and risk analytics, supporting major institutions worldwide. They are known for their commitment to innovation and excellence in the financial technology sector. The organization fosters a collaborative culture that values professional growth and technical expertise.

Responsibilities

• Own end-to-end production monitoring of AI/ML-enabled operational processes including drift and anomaly detection.
• Establish and maintain human-in-the-loop review protocols and escalation procedures.
• Drive the team-wide automation backlog to improve operational efficiency.
• Build and maintain dashboards, automated alerts, and AI-assisted investigation tools.
• Serve as the primary escalation point for high-severity incidents and lead root-cause analysis.
• Apply knowledge of counterparty credit risk concepts to interpret monitoring alerts and data quality issues.
• Manage work allocation, quality reviews, and cross-training for the team.
• Maintain comprehensive SOPs, runbooks, and control evidence for governance purposes.

Requirements

• 8-10 years of experience in technology operations or production support.
• At least 3-4 years of specific experience in AI Ops, MLOps, or AIOps-adjacent roles.
• Demonstrated experience monitoring AI/ML models in a production environment.
• Hands-on proficiency with AI Ops and observability tooling.
• Solid understanding of Counterparty Credit Risk concepts such as EPE/PFE, limits, and collateral.
• Proven experience in team leadership and people management.
• Strong stakeholder management and communication skills.
• Ability to manage SLAs and drive continuous improvement initiatives.

Skills

AI Ops, MLOps, Production Monitoring, Model Performance Monitoring, Anomaly Detection, Counterparty Credit Risk concepts, Team Leadership, Stakeholder Management, Automation, Incident Management, Root Cause Analysis, Data Quality Management, SLA Management