AI-Powered Process Analyst, EU Operations & Analytics

Amazon

Madrid

Presencial

EUR 60.000 - 90.000

Jornada completa

Hace 2 días
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Descripción de la vacante

Amazon Logistics, EU Central Operations Analytics is seeking a Process Analyst in Madrid, Spain to advance AI-powered automation and analytics across the delivery network. You will bridge business operations with technical execution, building intelligent dashboards, predictive models, and automated reporting that scale globally.

You'll collaborate with Operations, Data Science, and Engineering to translate operational needs into automated solutions, managing projects from design to deployment

Formación

  • Bachelor's or Master's degree in supply chain, business, engineering, finance or related quantitative field.
  • Experience managing projects.
  • Experience using Excel and data analysis.
  • Experience working with multiple groups of stakeholders.

Responsabilidades

  • Design and implement AI-powered automation solutions to streamline processes.
  • Develop machine learning models for predictive analytics and forecasting.
  • Build automated decision-support systems that scale across the network.
  • Create intelligent workflows reducing manual intervention and improving accuracy.
  • Partner with Data Science teams to deploy AI/ML solutions into production.
  • Evaluate and integrate emerging AI technologies to solve business challenges.

Conocimientos

Experience managing projects
Excel and data analysis
Stakeholder management

Educación

Bachelor's or Master's in supply chain, business, engineering, finance or related quantitative field

Herramientas

SQL
Python/R

Descripción del empleo

Amazon Logistics, EU Central Operations Analytics is seeking a Process Analyst in Madrid, Spain to advance AI-powered automation and analytics across the delivery network. You will bridge business operations with technical execution, building intelligent dashboards, predictive models, and automated reporting that scale globally.

You'll collaborate with Operations, Data Science, and Engineering to translate operational needs into automated solutions, managing projects from design to deployment

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