• Data Analyst

    Location LU-Luxembourg
    Posted Date 2 months ago(2 months ago)
    Job ID
    Amazon EU SARL
  • Job Description

    The European Transportation Network Design team is responsible for Amazon’s transportation network’s (truck lanes) connectivity across Europe that delivers billions of shipments each year. The team collaborates with multiple internal teams (e.g. Supply Chain, Finance, Tech, Retail) to create the optimal routes between origins and destinations to assure reliable package delivery to our customers at the fastest and cheapest way possible.

    We analyze enormous volumes of data to help Amazon think through how best to organize a quickly growing and changing network. We are constantly engaging with new kinds of problems, and use a wide range of tools to reach the right solutions, including Tableau, SQL, Python, Excel and simple common sense and business judgement.

    As a Transportation Analyst, you will help identifying opportunities and implementing solutions to improve systems, processes, and tools. You will be responsible for modeling complicated problems through the use of statistical, data mining and visualization techniques, and for working with a wide range of stakeholders across Amazon to implement the answers you identify. Success in Network Design requires not only strong analytical skills but also excellent interpersonal and communication skills. Network designing is uniquely concerned with connecting widely varying teams to a single vision and timeline, which requires very strong stakeholder management capabilities.

    The position is based in Amazon European headquarter in Luxembourg, a city widely known for its beautiful setting, livability, and highly international population, with foreign nationals making up over half of the population.

    In this position, the candidate will be responsible for
    • Ad-hoc data retrieval and analysis using relational databases, Excel and other data management systems
    • Supporting functional teams on the day-to-day execution of projects and initiatives with data
    • Build and maintain recurring metrics, reports, and dashboards
    • Driving small to medium projects that help build Amazon into the most customer-centric platform
    • Support definition and monitoring of long-term programs for automation or process excellence designed to mitigate risk for Amazon customers

    Basic Qualifications

      • Master’s degree or equivalent experience in Computer Science, Information Systems, or related business field.
      • Ability to take complex business problems and translate them into clear and accurate results
      • Proven analytical and quantitative skills and an ability to use hard data and metrics to back up assumptions, develop business cases, and complete root cause/ analyses
      • Ability to prioritize multiple concurrent projects while still delivering timely and accurate results
      • Demonstrated ability to work effectively with Data Engineers and BI Engineers to mine the right data sources efficiently and accurately
      • Strong verbal and written communications skills at an executive level that enable you to explain complex insights with clarity and precision

    Preferred Qualifications

    • 4+ years of experience as a Business/Financial Analyst, BI Engineer or Systems Analyst preferably in an internet-based company with large, complex data sources
    • Track record of strong interpersonal and communication (verbal and written) skills. Must be able to explain technical concepts and analysis implications clearly to a wide audience, including senior executives, and be able to translate business objectives into actionable analyses and contribute to documents
    • Experienced in developing insights across various areas of customer-related data: financial, product, and marketing
    • Proficient in multiple flavors of SQL (e.g. PostgreSQL, MySQL, Redshift)
    • Experience in data visualization platforms (e.g. Tableau, PowerBI, Quicksight)
    • Experience in developing applications (e.g. Python, Java) in a production environment
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