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Amazon Graduate Supply Chain Optimization Analyst

 

Location

Luxembourg

Who

Working towards or recently obtained a bachelor’s or master’s degree - ideally in Engineering, Computer Science, Mathematics, or Econometrics

Salary

Competitive

Deadline

Midnight, Sunday 9th August 2020

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.

DESCRIPTION

Are you passionate about leveraging data to deliver actionable insight that impacts daily business decision of Amazon in a promising new market segment?

Does the prospect of dealing with massive volume of data excite you?

Amazon is seeking a Supply Chain Optimization Analyst to join Amazon's AMXL team in Luxembourg or Munich. EU AMXL team is responsible for the end-to-end Heavy/Bulky journey in fulfillment, supply chain and transportation daily business and its strategic vision in Europe.

Amazon has culture of data-driven decision-making, and demands business intelligence that is timely, accurate, and actionable. During our day to day operations, tons of data is generated which is leveraged to take our important business decisions.
Our ideal candidate thrives in a fast-paced environment, relishes working with large transactional volumes and big data, enjoys the challenge of highly complex business contexts (that are typically being defined in real-time), and, above all else, is a passionate about data and analytics.

The position will provide you with an unforgettable working experience in a fast-paced, dynamic and international environment that values innovation.

The Supply Chain Optimization Analyst is a passionate advocate to drive operational efficiency with analytical and strong inter-personal skills. The candidate must be an effective communicator and be able to work with cross-functional teams including Fulfillment Center Operations, Transportation, Retail, and Senior Management.

This is a highly data-driven and highly analytical position which every business opportunity and decision will be based on data and facts. It is a very well-balanced position between daily operations and advanced analytics / research.

In this position you will:

  • Plan and shape EU AMXL inventory placement strategy;
  • Improve Supply Chain efficiency through mathematical modeling and data analytics
  • Carry out placement analysis on supply chain performance and system behavior
  • Adapt, build and maintain key placement metrics, perform root-cause analysis on abnormalities, and identify improvement opportunitites
  • Initiate and manage placement improvement projects and communicate with senior management;
  • Partner with software teams on tools, reporting standardization and system improvement;
  • Work across the EU and partner with the NA in a cross-functional environment, and maintain a strong communication process to ensure smooth and efficient flow of accurate information;

BASIC QUALIFICATIONS

  • Working towards or recently obtained a bachelor’s or master’s degree - ideally in Engineering, Computer Science, Mathematics, or Econometrics
  • Analytical based working experience;
  • Strong experience with Excel, SQL and data mining
  • Strong data analysis skills, ability to produce, interpret and draw conclusions from data
  • Experience in mathematical modeling (statistics, optimization, econometrics)
  • Strong communication and interpersonal skills;
  • Excellent written and verbal communication skills. Ability to simplify complex topics for broad audiences. The role requires effective communication with colleagues from computer science, operations research and business backgrounds.
  • Good team player and the ability to work with a wide cross-section of people in various locations
  • Creative and ideas-driven in finding new solutions/ designing innovative methods, systems and processes.
  • Ability to handle multiple competing priorities and projects in a fast-paced environment.

PREFERRED QUALIFICATIONS

  • Experience in Statistics / Machine Learning or general mathematical modeling
  • Familiarity and/or interest in Big Data Technology
  • Experience in data mining and analytics with R
  • Exposure to system dynamics and simulation - Some exposure to software development / coding (Python, C++, JAVA ...);

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