AI Data FP&A Analyst

Business Process & Definition Consistency  

• Drive metric and KPI definition consistency across the FP&A organization — establish and steward canonical definitions so that ARR, CMRR, NRR, GRR, and every board and internal KPI mean the same thing in every model, deck, and application.  

• Own the definitional source of truth — maintain living definitions, calculation logic, filter rules, and assumptions, and resolve conflicts when teams calculate the same metric differently.  

• Partner with FP&A to drive and standardize financial business process — mapping how financial data moves and how KPIs are produced across planning, close, and reporting cycles so the partnership yields repeatable data and insights rather than one-off analysis.  

• Translate process and definitions into requirements engineers can build against, and validate that what they implement matches business intent.  

AI Application Development (Claude)  

• Build and ship Claude-powered applications that operationalize SaaS FP&A metrics and KPIs — turning manual, spreadsheet-bound financial analysis into governed, self-service, on-demand intelligence.  

• Own the full build loop — prompt engineering, structured outputs, tool use, and iterative refinement — to produce reliable applications for finance use cases such as variance narration, forecast Q&A, KPI lookups, and board-metric explanations.  

• Build against the R365 platform stack (Snowflake → dbt → Cortex Analyst → Claude), wiring applications to governed semantic models and approved metric definitions so outputs are always tied to the source of truth.  

• Instrument and document application behavior — prompt logic, tool contracts, and output expectations — so solutions are auditable, maintainable, and transferable across the team.  

SaaS FP&A Metrics & KPI Development  

• Partner with the FP&A team to define and build board-level and internal KPIs — translating financial intent into precise, defensible metric definitions the whole organization can rely on.  

• Bring deep fluency in SaaS FP&A metrics — ARR, CMRR, NRR, GRR, bookings, churn, magic number, CAC/LTV, Rule of 40 — including how each is calculated, how they interrelate, and how they present to the board.  

• Ensure definitions are reflected consistently in the semantic layer — partnering with engineers on implementation so one metric carries one definition across planning, reporting, applications, and executive materials.  

• Support planning and reporting cycles — budget vs. actual vs. forecast variance, monthly and quarterly close validation — by making the underlying metrics fast, accurate, and explainable.  

FP&A Partnership & Business Context  

• Partner closely with Finance, Accounting, and business stakeholders through structured discovery to understand planning workflows, reporting needs, and the questions leaders are trying to answer.  

• Surface and escalate gaps between stakeholder needs and current platform capabilities, with clear written context for the engineering team.  

• Bridge communication between finance users and engineers, translating requirements and feedback in both directions.  

• Cross-Functional Collaboration  

• Deliver clear, well-organized applications and analyses to business partners, with support from senior team members for executive-facing presentations.  

• Participate in workshops, requirement sessions, and team check-ins to align on priorities and share progress.