Amazon Leo is building the infrastructure to deliver high-speed broadband connectivity to hundreds of millions of underserved people worldwide—and we need a finance professional who can measure whether our marketing investments are accelerating that mission. This is a ground-floor opportunity to shape how one of Amazon’s largest and fastest-growing businesses quantifies marketing impact at unprecedented scale.
This isn’t a traditional FP&A seat. You’ll sit at the intersection of AI-powered finance, marketing measurement science, and cross-functional strategy—partnering directly with measurement, product, and data engineering leads to build ROI frameworks from scratch. You’ll leverage Amazon’s industry-leading AI tools to automate processes that consume weeks at other companies, freeing you to focus on the work that matters: translating complex data into decisions that drive global marketing investment.
This role is a launchpad. Leo’s pre-launch position means increasing responsibility comes quickly for those who deliver, and your AI-forward skill set positions you for leadership opportunities across one of Amazon's core investment areas.
Key job responsibilities
Build ROI frameworks for marketing investments across all channels — including attribution modeling, incrementality testing, and marketing mix modeling — partnering with measurement science teams to align methodologies with financial rigor.
Drive timely, high-quality deliverables across concurrent workstreams including monthly business reviews, quarterly forecasts, and ad-hoc strategic analyses that inform executive decision-making.
Develop scalable financial models and tools that address complex business questions with limited oversight, delivering insights that directly influence multi-million-dollar investment decisions.
Leverage AI tools (Amazon Quick Suite, Amazon Bedrock, automated reporting workflows) to deliver efficient financial processes, redirecting capacity toward high-impact strategic analysis.
Partner cross-functionally with measurement science, product, data engineering, and horizontal marketing finance teams—representing financial insights with intellectual honesty and challenging assumptions respectfully when the data tells a different story.
Proactively explore emerging AI methodologies and automation opportunities, embracing ambiguity as an invitation to innovate and pursuing knowledge beyond immediate requirements.
