Lead Operational and AI Risk Manager

Accountabilities:: Analyze data from multiple sources to identify trends, anomalies, emerging risks, and areas requiring management attention, while developing clear reports, dashboards, metrics, and presentations for risk leaders and senior stakeholders. Assess business processes, operational activities, policies, controls, monitoring practices, and organizational changes to determine whether risks are appropriately managed and safeguards are operating as intended. Lead cross-functional initiatives involving Risk, Technology, Compliance, Audit, and business teams, supporting regulatory commitments, remediation programs, strategic priorities, and other complex risk initiatives. Provide independent oversight of models and analytical tools, evaluating model design, inputs, outputs, performance, limitations, monitoring practices, and documentation through a risk-based approach. Lead the independent validation of an AI- and LLM-enabled regulatory model, applying model governance and validation methodologies while serving as a subject matter expert in responsible AI practices. Apply structured LLM evaluation techniques such as benchmark testing, output consistency checks, adversarial prompting, and bias assessment to evaluate model reliability and suitability for regulatory use. Prepare clear validation and risk documentation covering methodologies, findings, limitations, conclusions, and recommended actions in formats suitable for regulatory review. Use AI tools in day-to-day risk activities, including research, analysis, and drafting, while identifying opportunities to improve the efficiency and quality of risk oversight through AI-enabled workflows. Assess emerging AI technologies and associated risks and contribute to governance considerations and practical implementation guidance as AI capabilities continue to evolve. Analyze fraud prevention, detection, monitoring, and response practices using available data, identifying trends, gaps, emerging concerns, and opportunities to strengthen program effectiveness. Support regulatory examinations, internal reviews, remediation efforts, and time-sensitive risk initiatives while independently managing complex assignments from problem definition through recommendations and implementation support. Build productive relationships across business, technology, compliance, audit, and risk functions, challenging assumptions constructively and influencing stakeholders through expertise, sound judgment, and practical problem solving. Requirements: Bachelor’s degree in business, finance, economics, mathematics, statistics, data analytics, information systems, risk management, or a related field, with at least 7 years of relevant experience in risk management, fraud, model oversight, data analytics, or a related discipline. Professional experience within banking, fintech, payments, or another regulated financial services environment, with a strong understanding of operational risk and business controls. Demonstrated ability to locate, interpret, analyze, and communicate data, translating complex findings into practical business insights and recommendations. Experience evaluating business processes, controls, risk management programs, fraud activities, models, statistical analyses, or performance monitoring is highly valuable. Experience supporting regulatory examinations, internal audits, remediation programs, or other regulatory and risk-focused initiatives is preferred. Strong problem-solving skills, intellectual curiosity, adaptability, ownership, and the ability to independently navigate ambiguous or complex assignments. Excellent written and verbal communication skills, including the ability to explain technical, analytical, and risk-related concepts clearly to non-technical audiences. Strong stakeholder management skills and the ability to collaborate across organizational boundaries and influence outcomes without direct authority, particularly within a remote environment. Comfortable using AI tools as part of everyday work, including large language models and AI-assisted research or analytical tools, with a demonstrated interest in applying AI to improve risk oversight. Familiarity with LLM evaluation techniques such as benchmark testing, output consistency assessment, adversarial prompting, and bias analysis is preferred, particularly in a model validation or oversight setting. Experience with SQL, Python, Power BI, Tableau, or similar data analysis, visualization, reporting, or governance tools is beneficial. Ability to manage competing priorities while maintaining high-quality, timely deliverables and strong follow-through. Must be legally authorized to work in the United States without current or future visa sponsorship and able to meet the role’s U.S. location requirement. Benefits: Fully remote position available anywhere in the United States. Full-time regular employment opportunity. Targeted base salary of $97,100–$145,500 per year , with final compensation determined by qualifications, expertise, and geographic location. Opportunity to work at the intersection of operational risk, data analytics, model governance, fraud risk, and emerging AI technologies. Broad cross-functional exposure to Risk, Technology, Compliance, Audit, and business stakeholders. Opportunity to contribute to responsible AI adoption and the development of AI-enabled risk management practices. Inclusive and accessible hiring process, with reasonable accommodations available upon request. No visa sponsorship is available; candidates must already have authorization to work in the United States without requiring current or future sponsorship.