Bellevue, WA, US
9 hours ago
Finance Manager - SCOT Automated Inventory Management , SCOT AIM Finance
The Supply Chain Optimization Technologies (SCOT) team sits at the core of Amazon's global supply chain — determining what inventory to buy, when to buy it, how much to order, where to position it, and how to recover value from unproductive inventory — all to delight customers while meeting Amazon's business objectives. Operating at massive scale across hundreds of product lines and billions of dollars of worldwide inventory, SCOT's fully in-house, automated planning and optimization systems are among the most sophisticated in the world. Finance within SCOT is a high-impact function, partnering directly with AI and machine learning engineers, scientists, product managers, and operations leaders to shape strategy, drive investment decisions, and deliver measurable improvements to Amazon's supply chain economics.

--The Role--

We're looking for a Finance Manager to serve as the financial partner for our Automated Inventory Management portfolio — a suite of systems that determine whether the right inventory is available, in the right place, in the right condition, across Amazon's global fulfillment network.

You'll serve as the dedicated finance owner for this portfolio end-to-end — with high agency, a direct line to the thought leaders defining Amazon's worldwide supply chain strategy, and the autonomy to drive investment decisions at a scale few finance roles can match.

We seek a candidate who is curious about how algorithms and automated systems drive business outcomes — comfortable interrogating model inputs, challenging assumptions, and asking "is this optimizing for the right thing?" You thrive in ambiguity, move quickly, and have a track record of building financial frameworks that help leadership make better choices.

Key job responsibilities
- Partner with Science and Product teams to develop financial strategies and drive controllership across our Automated Inventory Management systems, ensuring technology investments deliver maximum long-term free cash flow and measurable improvements to supply chain efficiency
- Navigate high degrees of ambiguity to build financial models that evaluate multi-million dollar technology investments and their impact on inventory placement, availability, and cost to serve
- Conduct rigorous financial assessments of identified inventory defects — including entitlement analysis, estimation accuracy, and opportunity costs — translating findings into measurable P&L impact across the network
- Build and maintain metrics and audit mechanisms to evaluate algorithmic decision outcomes, flagging when models underperform and surfacing data-driven recommendations to course-correct
- Develop compelling narratives and financial analyses for executive reviews
- Leverage AI agents, GenAI assistants, and AI-powered data platforms to accelerate analysis, improve productivity, and continuously explore new ways to deliver higher-quality insights faster

A day in the life
This role sits at the intersection of finance, technology, and supply chain strategy. You'll spend your time working shoulder-to-shoulder with operations research scientists, product managers, and engineers — engaging in model design discussions, stress-testing algorithmic assumptions, and translating system behavior into financial narratives that drive strategic decisions. No two days look the same: one day you're building a financial framework to evaluate a new algorithm with an engineer; the next you're presenting findings in a VP-level review where the outcome shapes how Amazon invests in its inventory infrastructure.

About the team
The AIM Finance team is the financial voice for a portfolio of AI-driven systems that make millions of inventory decisions every day — and our job is to make sure those decisions translate into real P&L outcomes. We are a small, high-ownership team where everyone follows their work all the way through, from the data to the executive narrative.

The culture is direct, curious, and intellectually honest. We work shoulder-to-shoulder with scientists, engineers, and product managers, ask hard questions, and show up as strategic equals.
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