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.