Senior AI Governance Analyst

Verisk Analytics is seeking a Senior AI Governance Analyst to support the responsible, ethical, transparent, and well-controlled use of artificial intelligence across the enterprise as Verisk operationalizes its AI Governance Platform and matures its AI Governance Workflow. Reporting to the Director, AI Governance Lead within the Chief Data Office, this individual contributor will manage the day-to-day execution of AI use case intake, initial risk triage, stakeholder coordination, platform administration, AI Governance Board preparation, decision tracking, ongoing monitoring, reporting, and user enablement. This person will help business, product, technology, and data science teams navigate governance requirements; ensure submissions are complete and routed to the appropriate reviewers; maintain accurate and audit-ready records; and follow approvals, conditions, exceptions, and remediation items through closure. This role will partner closely with Legal, Privacy, Compliance, Information Security, Data Governance, Procurement, Vendor Management, Third-Party Risk, Enterprise Risk, Audit, Technology, Product, Data Science, and business stakeholders. The successful candidate will be highly organized, comfortable multi-tasking and prioritizing, able to understand and document AI system details, and a critical thinker skilled at translating governance requirements into practical steps for business and technical teams . Acknowledging that AI governance is an evolving discipline, you will work to confirm that our global AI inventory is accurate, transparent, and in-line with the dynamic landscape of AI regulation and measurement. This role will be Hybrid in our Jersey City, NJ location. AI Use Case Intake, Triage, and Workflow Operations Serve as an operational point of contact for teams submitting AI, machine learning, generative AI, automated decisioning, and third-party AI use cases for governance review. Review submissions for completeness, clarity, and data quality, including business purpose, intended users, affected customers, data sources, model or solution type, third-party involvement, deployment approach, human oversight, and potential regulatory or reputational impact. Apply established intake and triage criteria to support preliminary risk classification, identify required evidence, and route use cases to the appropriate Legal, Privacy, Compliance, Information Security, Data Governance, Procurement, Third-Party Risk, and other reviewers. Guide requesting teams through documentation, risk assessments, stakeholder reviews, control requirements, approval steps, conditions of approval, monitoring obligations, and change or re-review requirements. Manage the active case queue, follow up on missing information and overdue reviews, track service-level expectations, identify bottlenecks, and escalate aging, high-risk, or unresolved matters to the Director. Track AI use cases from initial intake through review, board decision, implementation, monitoring, remediation, periodic reassessment, and closure. AI Governance Platform Administration and Data Quality Administer day-to-day records and workflows within the AI Governance Platform under the direction of the Director, AI Governance Lead. Maintain AI inventory records, intake forms, questionnaires, assessments, risk classifications, stakeholder reviews, approval records, evidence, controls, conditions, exceptions, remediation items, monitoring records, and reporting fields. Support platform configuration, user acceptance testing, release validation, workflow changes, conditional routing, notifications, dashboards, reports, user access, and self-service capabilities. AI Governance Board and Stakeholder Coordination Support AI Governance Board operations, including agenda planning, meeting scheduling, case prioritization, presentation preparation, reviewer follow-up, minutes, decision logs, record keeping, and action tracking. Capture and communicate Board decisions, conditions of approval, exceptions, required controls, remediation commitments, re-review triggers, and evidence requirements to use case owners and reviewers. Maintain audit-ready evidence of submissions, assessments, reviews, approvals, exceptions, decisions, communications, and follow-up actions. Ongoing Monitoring, Conditions, and Remediation Track post-approval conditions, exceptions, remediation plans to completion, periodic review dates, owner attestations, monitoring evidence, material changes, incidents, and re-approval requirements. Escalate overdue, incomplete, or high-risk items and support the Director in preparing issue summaries and recommended next steps for the AI Governance Board or other oversight groups. Assist with use case closure, archival, decommissioning, and inventory updates when AI systems are retired or no longer in scope. Reporting, Metrics, and Continuous Improvement Develop recurring and ad hoc reports for the Director, Chief Data Office, AI Governance Board, senior leadership, risk committees, business stakeholders, and other internal audiences. Track and report metrics such as AI use case volume, review status, approval cycle time, aging, risk tier, business unit participation, reviewer turnaround, conditions, remediation items, policy exceptions, and Board decisions. Analyze workflow trends and bottlenecks, identify opportunities to simplify, automate or improve governance activities, and support implementation of approved process improvements. Bachelor's degree in Computer Science, Artificial Intelligence, Information Systems, Business, Risk Management, Compliance, Privacy, Public Policy, or a related field, or equivalent practical experience. Four to six years of relevant professional experience in AI governance, data governance, model governance, technology governance, risk management, compliance, privacy, audit, technology controls, data science operations, product governance, program management, or a related field. Hands-on experience operating a structured intake, risk assessment, approval, inventory, issue-management, remediation, or control-evidence process in a complex organization. Comfortable with new technologies, some understanding of AI, machine learning, generative AI, automated decisioning, data science workflows , AI system lifecycle risks, and responsible AI principles. Ability to understand and document an AI use case’s business purpose, users, data, model or solution design, third-party dependencies, human oversight, outputs, potential impacts, and control requirements. Experience coordinating cross-functional reviews involving business, product, technology, data, Legal, Privacy, Compliance, Information Security, Risk, Procurement, or Audit stakeholders. Experience supporting enterprise AI governance platform implementation or GRC systems , workflow rollout, process redesign, or governance operating-model change. Preferred: Attained or interest in attaining the AI Governance Professional (AIGP) certification #LI-EA1