AI Analyst

Job Summary We are seeking a detail-obsessed, data-driven expert to serve as the guardian of accuracy and operational team lead for our Sales & Finance AI chat assistants. This role combines hands-on technical rigor with team leadership - you will design validation frameworks, partner with data engineering teams, and ensure every metric the AI surfaces - especially Bookings and Revenue - is accurate, consistent, and trustworthy. You will lead incident response on any data accuracy or hallucination event. Beyond quality, this role serves as the bridge between Finance users, executive stakeholders, and technical development teams - translating business requirements into AI-enabled solutions, ensuring Finance AI capabilities align with business goals, and leading a small team of analysts to deliver on the program's mission. You will set the quality bar, drive prioritization, coordinate across cross-functional partners, and represent the team in stakeholder forums. Core Responsibilities Team Leadership Lead and coordinate with analysts - set priorities, review deliverables, mentor team members, and drive the operating rhythm Drive the team's operating rhythm - standups, sprint planning, retrospectives, and weekly status reporting Serve as primary point of contact for PMO, IT, and Finance stakeholders on delivery matters Make prioritization and trade-off decisions across enhancements, bugs, testing, and adoption Requirements & Quality Assurance Gather business requirements; write clear user stories; translate Finance needs into AI solution specs referencing Snowflake tables and business logic Own the AI quality framework - test strategies, pass/fail criteria, and quality standards for AI-generated responses Oversee UAT, regression, and release testing; personally validate high-risk and executive-facing outputs Coordinate business sign-off before production releases Hallucination Prevention & Incident Response Own the hallucination prevention strategy - validation plans, monitoring protocols, and escalation procedures Lead incident response - rapid root cause analysis across source data, pipeline, Snowflake, and AI layers; document post-mortems with preventive measures Catalog high-risk use cases and maintain continuous quality monitoring Core Responsibilities Executive Use Cases & Data Governance Lead design and validation of executive-focused use cases; ensure outputs meet C-suite precision and tone standards Own data validation framework; ensure metric consistency against official Finance reporting Support audit, compliance, and AI governance requirements - maintain explainability and traceability Adoption & Operations Drive adoption strategy - oversee onboarding, training, communications, and user feedback synthesis Lead bug triage and coordinate resolution with IT/Engineering; manage release rollouts and hypercare Required Qualifications Bachelor's…