Product Manager, Americas DSP Capacity Planning

There are over 3000 Delivery Service Partners (DSPs) worldwide that delight customers every day as the chief delivery option in Amazon's Last Mile space,. The tools that decide how much DSP capacity we need, where we need it, and how we schedule and allocate routes against it are what make that possible at scale. This role owns a core part of the worldwide capacity technology roadmap that powers those decisions.

This is a builder role at the frontier of speed delivery. As Amazon pushes to deliver more packages in faster timeframes, the planning and allocation tools have to evolve to support entirely new forms of delivery and new package types. You will help build the technology that enables our delivery partners to meet those speed commitments, and you will enhance our existing scheduling and route allocation tools so they can flex to these new models rather than being rebuilt each time demand changes shape. You will also generate and run new pilots that optimize how we deliver, partnering with tech, engineering, and science teams to launch them and then scale the ones that work.

The defining characteristic of this role is that it is worldwide by design. We are not building tools for one region and porting them later. We are designing tools from the start so that any region in the world can adopt them and configure them to local needs. That means you will go deep in learning what actually matters to regions around the globe, where the planning realities differ, and what has to be configurable versus standardized. You will translate that understanding into products that hold up everywhere.

This is an ideal role for a product manager who wants to build globally scaled technology, work shoulder to shoulder with engineering and science, and sit at the leading edge of how Amazon reinvents delivery speed.

Key job responsibilities

• Own the worldwide capacity technology roadmap
• Build technology that enables our delivery partners to meet fast delivery commitments, including same-day and sub same-day delivery.
• Enhance existing scheduling and route allocation tools to support new forms of delivery and new package types, rather than rebuilding them for each new model.
• Generate new pilots that optimize delivery, and partner with tech, engineering, and science teams to launch and scale the ones that prove out.
• Design tools to be worldwide by default, built so any region can adopt them and configure them to local needs.
• Go deep in learning what matters to regions around the world, and translate those differences into products that hold up across geographies.
• Partner with upstream volume planning functions and downstream field execution teams to make sure the tools reflect real planning inputs and real operational constraints.
• Work cross-functionally with field operations, functional leaders, and science partners to drive influence and adoption of your products across the capacity planning space.

A day in the life
You spend your day at the intersection of product, engineering, and science. You might start reviewing how a scheduling tool behaves under a new delivery model, then work with an engineering and science partner to shape a pilot that optimizes route allocation for a new package type. Later you may be on a call with a region on the other side of the world, learning why their planning reality differs and what your product needs to make configurable. You are constantly moving between building for the specific problem in front of you and designing for a worldwide standard.

About the team
Team members need to both know their data and know their partner teams. Everyone on this team partners with upstream planning teams to understand what drives volume variability, then earns trust with downstream field and regional teams to build alignment on how we solve it. We are increasingly at the forefront of Amazon's partnership with data science as we expand into new programs, new markets, and new delivery speeds. The team is always encouraged not to find band-aids for one-off problems, but to build new mechanisms that solve the global underlying issue.