{"id":1440,"date":"2026-06-27T21:04:37","date_gmt":"2026-06-27T21:04:37","guid":{"rendered":"https:\/\/coderseditor.com\/itjobs\/job\/data-scientist-network-planning-optimization-world-wide-supply-chain-optimization-technology\/"},"modified":"2026-06-27T21:04:37","modified_gmt":"2026-06-27T21:04:37","slug":"data-scientist-network-planning-optimization-world-wide-supply-chain-optimization-technology","status":"publish","type":"job_listing","link":"https:\/\/coderseditor.com\/itjobs\/job\/data-scientist-network-planning-optimization-world-wide-supply-chain-optimization-technology\/","title":{"rendered":"Data Scientist, network planning optimization world wide, Supply Chain Optimization Technology"},"content":{"rendered":"

Data Scientist, network planning optimization world wide, Supply Chain Optimization Technology Overview<\/h2>\n\n\n\n\n\n\n\n\n
Company Name<\/strong><\/td>\nAmazon<\/td>\n<\/tr>\n
Job Role<\/strong><\/td>\nData Scientist, network planning optimization world wide, Supply Chain Optimization Technology<\/td>\n<\/tr>\n
Qualifications<\/strong><\/td>\nNot Specified<\/td>\n<\/tr>\n
Category<\/strong><\/td>\nIT Jobs<\/td>\n<\/tr>\n
Job Type<\/strong><\/td>\nFull Time<\/td>\n<\/tr>\n
Location<\/strong><\/td>\nLondon<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

This role sits within Amazon\u00e2\u0080\u0099s Supply Chain Optimization Technology organization and focuses on improving how products are planned and moved through the global fulfillment network. The work is centered on building scientific solutions that help Amazon decide where inventory should be positioned, how products should flow through the network, and how to balance customer experience, operating cost, and carbon impact across multiple regions such as Europe, Japan, India, and beyond.<\/p>\n

The position is part of a highly collaborative environment where you will work with scientists across Amazon, technical teams building planning and execution tools, and business and operational partners who help define priorities and provide the inputs needed to solve complex supply chain problems. The role calls for strong analytical thinking, a deep scientific mindset, and the ability to communicate clearly and influence decisions across functions and levels of seniority.<\/p>\n

What you will do<\/h3>\n
    \n
  • Develop advanced mathematical approaches that improve inventory placement and product movement decisions across the supply chain network.<\/li>\n
  • Create statistical and optimization models that support supply chain planning when demand and operating conditions are uncertain.<\/li>\n
  • Contribute to the design of fulfillment strategies that improve customer experience while reducing cost and environmental impact.<\/li>\n
  • Work with Amazon\u00e2\u0080\u0099s worldwide scientific community to shape network planning approaches for global operations.<\/li>\n
  • Partner with engineering teams to build optimization tools used in network flow planning and execution systems.<\/li>\n
  • Work closely with business and operations stakeholders to identify opportunities, gather requirements, and solve planning challenges.<\/li>\n
  • Manage several important projects at once and keep them moving effectively.<\/li>\n
  • Translate analytical results into clear recommendations for senior stakeholders using technical documents, business-facing papers, or similar formats.<\/li>\n
  • Apply large language models to make optimization solutions easier to explain and to encourage broader use by supply chain planners around the world.<\/li>\n<\/ul>\n

    What Amazon is looking for<\/h3>\n
      \n
    • Strong analytical capability and a solid scientific background.<\/li>\n
    • Excellent written and verbal communication skills, with the ability to influence people across different business functions and seniority levels.<\/li>\n
    • Comfort working in a fast-paced setting where attention to detail matters.<\/li>\n
    • Experience using data scripting languages such as SQL, Python, or R, or equivalent statistical or mathematical tools such as SAS or Matlab.<\/li>\n
    • Prior experience working in a data scientist role.<\/li>\n
    • Experience building and applying statistical models, including examples such as multinomial logistic regression.<\/li>\n
    • Experience working collaboratively with data engineers and business intelligence engineers.<\/li>\n<\/ul>\n

      Nice to have<\/h3>\n
        \n
      • Experience with data visualization tools such as Tableau, Quicksight, or similar products.<\/li>\n
      • Experience managing data pipelines.<\/li>\n
      • Experience leading others and mentoring teammates on a data science team.<\/li>\n<\/ul>\n

        Additional information<\/h3>\n

        Amazon describes itself as an equal opportunities employer and says that diversity is central to its success. Hiring decisions are made on the basis of skills and experience. The company also emphasizes its inclusive culture and its focus on delivering the best outcomes for customers.<\/p>\n

        Applicants are directed to Amazon\u00e2\u0080\u0099s privacy notice for information about how candidate data is collected, used, and transferred. If you need a workplace adjustment or accommodation during the application, interview, or onboarding process, Amazon provides a dedicated accommodations resource for support.<\/p>\n

        The posting is for a role in London, United Kingdom, and the page does not describe a remote or hybrid working arrangement.<\/p>\n\n

        Degree Requirement:<\/strong> Not Specified<\/p>\n

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