Analyst, Supply Chain, EU Long Term Planning

Amazon; Clichy; Sur place; EUR 55 000 - 85 000; Plein temps

Résumé du poste

Amazon is seeking an Analyst in Long Term Planning - Supply Chain Analytics to steer topology and planning decisions across Europe, balancing cost, speed, and customer experience.

You will develop analytical models, build dashboards, and partner with engineering to deliver automated planning tools while managing project timelines.

The role emphasizes 75% analytics and 25% project management, with collaboration across Topology, Regionalization, and Planning teams.

Qualifications

• Currently enrolled in or received a Master’s or Bachelor’s degree in Math, Engineering, Science or Business.
• Experience in analytical tasks or projects, working with data.
• Experience in a finance role leading a project or program and partnering with multiple stakeholders.
• Experience engaging, verbally and in writing, with internal and external stakeholders to convey complex ideas in a clear, concise manner.

Responsabilités

• Develop, own, and maintain analytical frameworks and models for topology and network planning across Europe.
• Conduct deep-dive analyses on regionalization strategies to drive long-term planning recommendations.
• Build and enhance data pipelines, dashboards, and automated reporting for KPIs.
• Perform scenario modeling to quantify impact of network changes on cost-to-serve and delivery speed.
• Identify improvement opportunities and inefficiencies in the current network topology with quantified business cases.
• Partner with Science and Engineering teams to translate findings into scalable planning tools.
• Drive end-to-end delivery of analytical projects from scoping to stakeholder communication.
• Coordinate cross-functionally with Topology, Regionalization, Planning, and other teams.

Connaissances

Data analysis

Stakeholder management

Finance project experience

Presentation skills

Formation

Master's/Bachelor's degree in Math/Engineering/Science/Business

Description du poste

Description

As an Analyst in the Long Term Planning - Supply Chain Analytics team, you will be responsible for steering our key topology/planning decisions in order to provide the best speed and cost to the customers, and improve customer experience across a wide range of functional areas, as well as business focused views. Our portfolio ranges across Topology, Regionalization, Planning, and other initiatives in collaboration with the LTP org.

The role includes 75% of analytical activities management and 25% project management.

Key job responsibilities

• Develop, own, and maintain analytical frameworks and models that steer topology and network planning decisions across the European First Mile network, optimizing for cost, speed, and customer experience.
• Conduct deep-dive analyses on regionalization strategies, evaluating trade-offs between local fulfillment, cross-border flows, and in-stock positioning to drive long-term planning recommendations.
• Build and enhance data pipelines, dashboards, and automated reporting solutions that provide visibility into key topology and planning KPIs, enabling data-driven decision-making for senior leadership.
• Perform scenario modeling and simulations to quantify the impact of proposed network changes (e.g., new node openings, capacity shifts, flow rebalancing) on cost-to-serve and delivery speed.
• Identify improvement opportunities and inefficiencies in the current network topology through root cause analysis, surfacing actionable insights and quantified business cases for change.
• Partner with Science and Engineering teams to translate analytical findings into scalable, automated solutions and planning tools.
• Drive end-to-end delivery of analytical projects from scoping and requirements gathering through execution to stakeholder communication, ensuring alignment with LTP org priorities and timelines.
• Coordinate cross-functionally with Topology, Regionalization, Planning, and other partner teams to align on inputs, assumptions, and deliverables for shared initiatives.
• Manage project timelines, dependencies, and risks while navigating ambiguity and shifting priorities in a fast-paced environment.
• Communicate complex analytical findings to technical and non-technical audiences through clear narratives, written documents, and presentations that influence strategic direction.

About the team

• Operations is at the heart of the Amazon customer experience. Each action we undertake is on behalf of our customers, as surpassing their expectations is our passion. We improve customer experience through continuously optimizing the complex movements of goods from vendors to customers throughout Europe.
• The Supply Chain, Transportation Planning & Operational Excellence (EU STEP) is an organization responsible for the end-to-end flow of goods from our vendors and sellers to Amazon customers all over Europe, in order to ensure a speedy and reliable customer delivery in the cheapest way possible.
• Long Term Planning analytical teams are transversal centers of expertise, composed of engineers, analysts, and scientists. We are focused on Amazon most complex problems, processes and decisions. We work with fulfillment centers, transportation, finance and retail teams across the world, to improve our logistic infrastructure. We are obsessed by rethinking our advanced end-to-end supply chain to make our deliveries even faster.

Basic Qualifications

• Currently enrolled in or received a Master's (or Bachelor’s) Degree in Math, Engineering, Science or Business
• Experience in analytical tasks or projects, working with data
• Experience in a finance role leading a project or program and partnering with multiple stakeholders within a business, or experience making strategic business decisions and managing internal relationships
• Experience engaging, verbally and in writing, with internal and external stakeholders to convey complex ideas in a clear, concise manner

Preferred Qualifications

• Experience working in a fast-paced and ambiguous environment, or experience in creating process improvements with automation and analysis

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