Senior Financial Analyst, FP&A (AI First)

Senior Financial Analyst, FP&A (AI First)

Design, build and maintain the AI agents and automated workflows that carry the recurring FP&A load: variance analysis, first-pass commentary, cohort and retention analysis, board metric refreshes, and the routine data pulls underneath all of them. Use AI as a default part of your workflow, across analysis, modeling, reporting, and commentary, within our team practices and data-handling guidelines. Use Claude, which every employee here already has, to speed up analysis, automate recurring reporting, draft first-pass variance commentary, and pressure-test your own assumptions before numbers go out. Build the context these agents need in order to be reliable: metric definitions, documented data lineage from source system to report, and explicit rules for how each number is constructed. An agent is only as good as the context it can reach. Decide what should and should not be automated. Draw and defend the line between work an agent runs unsupervised, work an agent drafts for human review, and work that stays fully manual. Own the finance team's shared library of agents, prompts, skills and calculation templates. Treat it as a deliverable in its own right, versioned and documented, so that it keeps producing when you are on vacation. Own what the tools produce, review AI-assisted work to the same standard as your own, and know when a question needs judgment instead. Build the checks in: validation against source, reconciliation, and a review step that catches a wrong answer before it reaches leadership or the board. Raise the ceiling for the people around you. Some of your highest-leverage work will be enabling your business partners to answer their own questions rather than producing the analysis yourself. Planning and forecasting Prepare Own the annual budget and quarterly/monthly forecast updates, gathering inputs from department leaders. Maintain the company's financial model (revenue, expenses, headcount, and cash) and keep the key assumptions up to date. Structure it so that running a new scenario is a configuration change, not a rebuild. Run scenario analysis to help leadership weigh decisions, using AI to build and iterate on cases faster than a manual model rebuild allows, fast enough to be useful in the meeting where the decision is actually being made. Reporting Own the monthly reporting package: actuals versus budget and forecast, variance analysis, and commentary. AI-drafted first pass, then edited and owned by you. Help prepare materials for leadership and board meetings, including our key metrics and dashboards. Work with the accounting team during month-end close to make sure results are accurate and on time. Metrics and analysis Own our core SaaS metrics (ARR/MRR, net and gross revenue retention, churn, CAC, and LTV) and keep the definitions consistent. Look at customer, product, and segment profitability and take the findings to the people who can act on them. Build and maintain reports in our BI tools so teams can see the numbers they need, and so that analysts, dashboards and agents all draw on one trusted source rather than several competing ones. Working with the business Be the finance point of contact for Sales, Marketing, Product, and G&A, helping them manage budgets and understand spend. Partner with Data and Analytics to scope reporting needs, so what we build answers the right questions. Help evaluate the costs and benefits of proposed projects and investments. Handle ad-hoc analysis requests as they come up. A Little Bit About You A reliable instinct for when a machine-generated answer is wrong. This is a very important qualification for this role. Structured thinking: you can break a vague business question into defined, verifiable steps, which is the same skill that makes an agent work. Demonstrated use of AI tools in real finance work. You can walk us through something you automated or accelerated, and how you checked the output. Experience building AI-assisted workflows: prompt-based reporting, scripting, or connecting AI tools to finance data sources. 3–5+ years of experience in FP&A, corporate finance, or a similar analytical finance role. We weight demonstrated ability to build with AI as heavily as two additional years of conventional experience. Experience at a SaaS or subscription business, or willingness to get up to speed on the model. A good understanding of common SaaS metrics (ARR, retention, churn, CAC, LTV) and what drives them. Solid financial modeling and Excel/Google Sheets skills. Excel and Google Sheets are output formats here rather than the core skill; the core skill is breaking a FP&A question down precisely enough that an agent can run it reliably and repeatably. A working knowledge of the three financial statements and subscription revenue recognition. The ability to explain financial results clearly to people outside of finance. Comfort with ERP, planning, and BI tools (e.g. NetSuite, Cube, QuickSight, or similar). An understanding of how finance and business systems fit together and how data moves between them, and the ability to scope reporting needs with Data teams. A willingness to work in the open, documenting what you build so that someone else can run it. A Bachelor's degree in Finance, Accounting, Economics, or a related field.