Role Overview
The role will own the re‑engineering of the current automated forecasting model, Fleet Requirement Planning (FRP), to: (1) integrate new Amazon organization van requirements (e.g., Ship With Amazon (SWA) /Delivery Service Partner (DSP) Lite); (2) move to clustering, probability‑based modelling and agentic AI; (3) scale optimization models with objective function being the operational costs; (4) evolve the user interface from Excel based to a more friendly dashboard; (5) integrate new supply channels and netting logics within the model (e.g. van sharing, off‑season vans, vehicle multi‑use, etc.) to drive the related sourcing accordingly; (6) integrate seamless both upstream and downstream (approvals) processes; (7) scale Fleet Requirement Planning to Middle Mile; (8) support effectively critical business decisions (Capex/Opex, rental/lease/cross‑country transfer, vehicle type mix, asset utilization, etc.) based on risk assessment and long‑term constraints.
Responsibilities
A day in the life:
- Design and develop scalable Fleet demand modelling.
- Integrate closely with finance business partners to ensure plans are efficient and meet peak demand, and to ensure an efficient ordering process.
- Define and own Fleet Demand forecasting accuracy metric.
- Be accountable for the timely “buy in” from VP/Senior Stakeholder about the significant Fleet CAPEX investment and OPEX decisions; consolidate input from a different set of stakeholders and ensure fleet plans always consume the latest available assumptions.
- Drive the transition to electrification (EV planning Business As Usual) and integration of MoT into Fleet Requirement Planning.
- Extend FRP process to new business customer organization (SWA, DSP Lite) and countries to be launched over the next years.
Team & Culture
The EU Amazon Logistics (AMZL) Fleet Planning & Analytics team operates within Global Fleet & Products. We are responsible for EU AMZL fleet requirement definition to source Armada/Rentals, short‑term deployment scheduling, and business intelligence support—with the north star to scale fleet capacity efficiently. The Fleet Demand planners within FPA team are comparable to other companies’ “Demand Planner” profiles, but face the peculiar challenges of integrating upstream planning cycles (e.g., from SCOT/Top Line to LTP/TL disaggregation, from MRP to DA Labour Plan, and DSP diversification planning) to create demand plans for diesel (ICE), Electric Vehicles (EV), Long/Short Wheel Base (LWB/SWB) vans across Europe for long (+3y) and medium term.
Experience & Qualifications
- Experience implementing pragmatic operations solutions to solve problems such as the scheduling, routing, assignment, facility location, or lot‑sizing problem.
- Experience with algorithm and model development work for large‑scale applications.
- Experience with technology transformation initiatives.
- Experience leading cross‑functional teams across engineering, operations, and field execution through launch readiness and go‑live phases, or experience with retrofits, launches, or automation deployments.
- Experience leveraging technology to drive process improvements.
- Experience in strategic planning.
- Experience solving complex problems quantitatively and developing actionable data‑driven business recommendations.
- Experience delivering results, setting strategy, and running a large volume and high‑profile business.
- Experience in technical support, or experience that includes strong analytical skills, attention to detail, and effective communication abilities.
- Experience with creating and improving a variety of processes across product types and teams.
- Experience coordinating complex products with stringent technical requirements, development cycles, and schedules.
- Experience working across teams and influencing teams that are not your own.
- Experience communicating results to senior leadership.
- Experience dealing well with ambiguity, prioritizing needs, and delivering measurable results in an agile environment.
- Experience prioritizing competing demands, scoping large efforts, and negotiating timelines.
- Knowledge of supply chain management concepts—forecasting, planning, sourcing, optimization, and logistics or equivalent.
- Master’s degree, or a Bachelor’s degree and experience with various machine learning techniques and parameters that affect their performance.
- Lean Six Sigma Green Belt or Black Belt certification.
- Experience with Six Sigma methodologies.
Equal Opportunity Statement
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build.
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