Process Improvement Specialist II, Long-Term Planning

AmazonLuxembourgOn-siteFull-timeJunior, 1–2 yearsListed 1 hour ago

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About this role

Description

Are you energized by turning complex supply chain data into decisions that customers feel at their doorstep? We are looking for a curious, data-driven Process Improvement Specialist to join our Long Term Planning team and steer First Mile network strategy across our European delivery network. Your analysis — built on SQL, statistical methods, data visualization, and generative AI — will directly support capital investment decisions (where and when to add fulfillment center capacity, retrofits, and building design) as well as operational decisions around staffing strategy and under-the-roof productivity.

This is a particularly exciting time to join: the team is actively integrating Same Day delivery into our First Mile topology strategy, opening up new problems to solve and new impact to drive. You will split your time between analytical work (roughly 75%) and cross-functional project management (roughly 25%), working with senior leaders on high-stakes recommendations that shape how we move goods across Europe.

Key job responsibilities
- Analyze First Mile network capacity, flow, and cost data using SQL, statistical modeling, and data visualization to build recommendations that inform capital and operational investment trade-offs across the European delivery network.
- Collaborate with partner teams to influence and maintain a roadmap of First Mile improvement projects, launching pilots for the most complex opportunities and building scale-up business cases that quantify benefits, risks, and required resources.
- Design and maintain analytics tools and dashboards — applying generative AI where it accelerates insight — to surface defects, track process performance, and extract actionable findings from pickup through fulfillment center injection.
- Lead regular business reviews with cross-functional stakeholders to monitor project progress, identify and remove bottlenecks, and drive alignment on priorities.
- Consolidate findings into concise, data-driven status updates and present recommendations to senior leadership, managing stakeholder expectations and adapting communication to your audience.

A day in the life
Imagine we need to decide whether a new fulfillment center in one region versus another best unlocks faster delivery for customers. You would own that question end to end: form a defensible first answer from existing data, pinpoint the injection volumes, line-haul lanes, and sortation readiness data that would confirm or challenge it, then quantify the speed benefit against capital and operating costs. You bring transportation, fulfillment center operations, and last-mile partners along as you work, and package everything into a clear recommendation for senior leadership. The expectation is a sound, numbers-backed decision in days — set up to refresh quickly and scale — not a perfect answer in a month.

About the team
Our Long Term Planning team sits within Amazon's European operations organization and is responsible for tackling the most complex supply chain problems and decisions. We are a group of engineers, analysts, and scientists who work across fulfillment centers, transportation, finance, and retail teams to continuously improve how goods move from vendors and sellers to customers throughout Europe.

Because the decisions you support carry significant capital weight, you will have regular exposure to senior leadership — an environment that sharpens your communication skills and professional confidence. We are an inclusive, collaborative team that values rigorous analysis and practical problem-solving as we rethink our end-to-end supply chain to make deliveries even faster.

Basic Qualifications

- Bachelor's degree or equivalent qualification in Engineering, Supply Chain, Economics or Business Administration
- Experience in analytical tasks or projects, working with data
- Bachelor's degree or equivalent qualification in Math, Engineering, Science or Business
- Experience making strategic business decisions and managing internal relationships, or experience in a finance role leading a project or program and partnering with multiple stakeholders within a business
- Experience engaging, verbally and in writing, with internal and external stakeholders to convey complex ideas in a clear, concise manner

Preferred Qualifications

- Master's degree in mathematics, engineering, statistics, computer science, business administration or a related field
- Experience working in a fast-paced and ambiguous environment

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