Senior Program Manager, Amazon Transportation Services (NEST) Science

Have you ever placed an order on Amazon and wondered how it got to you, or how it got to you so fast? Do you get excited thinking about the data and technology that power complex transportation networks? Then come join the Network Engineering, Scheduling and Technology (NEST) Science team within Amazon Transportation Services and help us innovate the way packages flow to our customers.

We are looking for a Senior Program Manager to drive the delivery and cross-functional execution of science-powered products that shape how Amazon schedules and moves packages across its Middle Mile transportation network. In this role, you will manage programs that sit at the intersection of Operations Research, Machine Learning, and Simulation, working closely with scientists, engineers, product managers, and business stakeholders to take models from prototype to production at scale. You will own the end-to-end execution of initiatives that directly influence how hundreds of thousands of truck movements are scheduled, how network configurations are optimized, and how decisions are made under uncertainty.

The ideal candidate is someone who can translate complex science and engineering workstreams into structured program plans, drive alignment across organizations with competing priorities, and keep high-impact initiatives on track from concept through launch. You are comfortable operating in ambiguity, can quickly build a working understanding of technical domains (optimization, forecasting, simulation), and know how to navigate a matrixed organization to unblock teams and accelerate delivery. You bring a bias for action, strong judgment on trade-offs, and the ability to communicate progress, risks, and recommendations to audiences ranging from scientists to senior executives.

Key job responsibilities

• Own end-to-end program management for science product initiatives, including planning, milestone tracking, risk management, and delivery across science, engineering, and operations workstreams
• Drive cross-functional execution of optimization and prediction models from pilot through productionization, coordinating across operations and tech teams
• Manage program dependencies and timelines for initiatives spanning multiple teams, including model development, engineering integration, A/B testing, and production deployment
• Facilitate alignment between science teams and business stakeholders, translating technical model capabilities and limitations into actionable business context
• Establish and maintain program mechanisms: status reviews, decision documents, escalation paths, and stakeholder communications for programs impacting network-wide planning
• Create and execute change management strategies to drive adoption of science-based tools and models across the organization
• Define success metrics and reporting frameworks to measure and communicate program impact, including financial savings, operational improvements, and model performance
• Build and maintain program documentation including technical specifications, implementation plans, pilot designs, and post-launch retrospectives
• Partner with Product Managers to translate science roadmap priorities into executable program plans with clear milestones and owner accountability
• Communicate program status, trade-offs, and recommendations to senior leadership through written narratives, business reviews, and operational updates

About the team

The Network Engineering, Scheduling, and Technology (NEST) Science Team prototypes, builds, and productionizes mathematical models that reduce transportation cost and improve customer experience in Amazon"s Middle Mile network. Equipped with techniques from Operations Research, Machine Learning and Simulation, these models are used to govern scheduling and equipment selection of hundreds of thousands of truck movements, optimize network configurations, determine the transit times between nodes, and simulate network flow under uncertainty for informed decision making. Our core team consists of Applied, Data, and Research Scientists along with Product Managers that come from diverse backgrounds.