Location
London

Hours
Full Time

Salary
Competitive, based on experience

About the Role
At Amazon, we strive to be the most customer-centric company on earth. One key area where we continuously raise the bar is in fulfilling and delivering orders quickly and accurately worldwide. The Fleet Process Excellence (FPE) team, part of EU Fleet Operations, drives measurable cost optimisation across our branded delivery fleet, operating across multiple European countries. We collaborate with internal Last Mile stakeholders and external partners including Delivery Service Providers (DSPs), Fleet Management Companies (FMCs), and Original Equipment Manufacturers (OEMs). We are seeking a Fleet Process Excellence Insights Manager to own the fleet cost insights pipeline end-to-end. This is a proactive role where you will identify cost optimisation opportunities, build data foundations to quantify them, and translate complex analyses into clear, actionable recommendations for Director and Regional leadership.

You will be the technical backbone of the FPE team, responsible for coding, automation, data solutions, and business intelligence. You will dive deep into large datasets covering fleet cost-per-package (CPP), vehicle off-road rates (VORR), and operational cost drivers to uncover significant savings opportunities. Success in this role requires high independence, strong communication skills bridging technical and non-technical audiences, and the ability to deliver results with minimal direction.

Key Responsibilities
- Own the fleet cost insights pipeline: design, build, and maintain automated data pipelines and reporting that serve as a single source of truth for fleet cost performance (CPP, VORR, cost-by-station, cost-by-DSP).
- Proactively identify cost optimisation opportunities using statistical analysis to detect trends, gaps, and savings levers; quantify impact and present actionable recommendations to senior leadership.
- Develop and maintain executive-ready performance dashboards synthesising large data volumes into clear narratives.
- Drive automation and tooling by building scalable, automated solutions (ETL pipelines, API integrations, serverless data processing) to reduce manual effort and improve data quality.
- Translate complex data insights for non-technical stakeholders, partnering with Regional Fleet Managers, Finance, and Operations leaders to enable informed decisions.
- Lead cross-functional data projects focused on reporting improvement, data standardisation, and process automation.
- Build and maintain data models and warehouse structures supporting scalable, repeatable analysis of fleet cost drivers.
- Collaborate with Finance teams to align cost data, validate savings estimates, and support business case development.

Experience
- Proven experience with large-scale data analytics and data warehousing.
- Proficiency with reporting and data visualization tools such as Quick Sight, Tableau, Power BI, or similar BI packages.
- Skilled in data modeling, warehousing, and building ETL pipelines.
- Experience communicating complex results to senior leadership and solving business challenges through accurate financial models, analysis, and actionable recommendations.
- Experience working in matrixed environments, influencing strategy, and collaborating across organizations.
- Experience in program management, logistics, operations, supply chain, or transportation is preferred.
- Experience in financial modeling, P&L management, quantitative roles, or engineering process re-engineering is advantageous.
- Familiarity with Big Data, DevOps, Security, Systems Administration, software development, or cloud technologies is a plus.

About You
- Strong independence and self-motivation with the ability to deliver results end-to-end.
- Excellent communication skills, able to bridge technical and non-technical audiences.
- Analytical thinker who can dive deep into data and translate insights into clear, actionable recommendations.
- Comfortable working in ambiguous environments and driving initiatives forward.
- Collaborative mindset with the ability to lead cross-functional projects and influence stakeholders.

Qualifications
- Bachelor's degree or higher in computer science, engineering, mathematics, operations, logistics, supply chain, or related field, or equivalent experience.
- Preferred qualifications include degrees in operations research, applied mathematics, theoretical computer science, or equivalent.
- Experience applying machine learning algorithms to operational data is a plus.
- Proven ability to build measures, metrics, and reporting solutions that support business-critical decisions.