Senior Financial Analyst, FAIM Finance (Amazon Ads)

Amazon Ads is building toward a future where an advertiser specifies a few marketing parameters (budget, success definition, which products to promote) and a set of AI agents handles the rest. The Full Funnel Agentic Intelligence and Models (FAIM) organization owns that bet: the Ads Nova agent, the Ads Nova model it reasons with, and the full-funnel campaign products that put them in front of advertisers. FAIM Finance is the team that answers whether the bet is paying off, and at what cost.

We are hiring a Senior Financial Analyst to own financial planning and analysis for this organization: the operating plan, the monthly actuals and forecast, the business reviews, and the models that translate agent and model usage into revenue and cost. This is a ground-up build. The products are new, the cost structure is GPU and compute heavy with inference costs that scale with every advertiser conversation, and the forecasting methods have to be invented rather than inherited. You will work alongside a small team of finance managers, business intelligence engineers, and data engineers, with regular exposure to the leaders who run FAIM and to senior leadership across Ads Finance. If you want a finance seat where the P&L looks nothing like a traditional advertising business and the decisions are still being made, keep reading.

What you'll own

The FAIM operating plan and forecast: annual planning (OP1/OP2), quarterly forecasts, and monthly actuals with variance analysis across revenue, headcount, and infrastructure spend
The business review mechanism: weekly, monthly, and quarterly reviews that leaders trust for accuracy and read for the story behind the number
Driver-based models that connect product usage (advertisers, campaigns, agent conversations, tokens, GPU hours) to revenue and cost to serve, for products with little or no history to extrapolate from
The investment cases: financial support for compute and GPU requests, headcount asks, and new product bets, including the analysis in documents that go to senior leadership

Key job responsibilities

Drive the planning cycle: build and maintain the FAIM financial model, consolidate inputs from Product, Engineering, and Science, and own the bridge between plan, forecast, and actuals
Run the monthly close analysis: explain variances, identify root causes, state the financial implication, and follow through on the actions that come out of it
Partner with product and engineering leaders to anticipate business needs, interpret trends, and evaluate the economics of new products, pricing, and infrastructure decisions
Build the models behind investment decisions (compute capacity, headcount, pricing) and write the financial sections of documents that senior leaders act on
Coordinate the business review mechanisms, ensuring reporting accuracy and clear communication of results and recommendations
Work with the team's business intelligence and data engineers so the finance data platform answers the questions the P&L raises; define what the business needs to measure and how it is read
Lead projects to automate, simplify, or scale finance processes, including AI-enabled tools that reduce manual work and defects
Uphold strong financial controllership: accurate accruals, clean cost allocation, and documented SOPs that let others pick up the work

We're looking for an analyst who brings

3+ years of finance, FP&A, or related analytical experience, and a bachelor's degree in finance, accounting, economics, business, or a related field
Strong financial modeling skills: driver-based forecasts, scenario analysis, and the attention to detail to make the numbers tie
Experience building financial and operational reports that inform decisions, and applying key performance indicators to explain what happened and why
Working SQL and advanced Excel fluency, with the habit of pulling your own data rather than waiting for it
Clear written and verbal communication, with the ability to explain a variance or a recommendation to a senior leader in plain language
Experience in advertising, software, or cloud infrastructure finance, especially with usage-based cost structures (compute, GPU, inference), is a plus
Python or equivalent for analysis and automation, and familiarity with QuickSight or similar reporting tools
Experience supporting a new product or 0-to-1 business where forecasting is built from drivers rather than trends
AI-native working style: using tools such as Kiro, Claude Code, or equivalent to automate recurring analysis and catch defects faster
Comfort operating in ambiguity, with a bias for action and the judgment to know when precision matters and when direction is enough