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 degree required

7+ years in Business Analysis, Finance Analytics, or FP&A Operations

2+ years team lead or coordination experience

Advanced SQL

2-3 years of Experience with AI-powered tools or conversational AI; strong understanding of LLM fundamentals and hallucination risks

Prompt Engineering certification or equivalent experience

Understanding of Finance metrics (Bookings, Revenue, or related)

Strong stakeholder management - comfortable engaging with Directors and above

Technical Skills Required

SQL / Snowflake: Advanced - complex queries, data lineage tracing, validation scripting

AI/LLM Concepts: Strong - RAG, prompt engineering, hallucination patterns, data grounding

Data Modelling: Strong - ERDs, star schemas, pipeline architectures

Abacus (or similar) – working knowledge

Familiarity with Agile/Scrum & BI Tools

Preferred Qualifications

Experience with Abacus, RAG architectures, or AI governance frameworks

Background in Finance AI transformation or digital initiatives