{"id":2579,"date":"2026-07-08T20:41:50","date_gmt":"2026-07-08T20:41:50","guid":{"rendered":"https:\/\/coderseditor.com\/itjobs\/job\/applied-scientist-prime-video-commerce-insights\/"},"modified":"2026-07-08T20:41:50","modified_gmt":"2026-07-08T20:41:50","slug":"applied-scientist-prime-video-commerce-insights","status":"publish","type":"job_listing","link":"https:\/\/coderseditor.com\/itjobs\/job\/applied-scientist-prime-video-commerce-insights\/","title":{"rendered":"Applied Scientist, Prime Video Commerce Insights"},"content":{"rendered":"

Applied Scientist, Prime Video Commerce Insights Overview<\/h2>\n\n\n\n\n\n\n\n\n
Company Name<\/strong><\/td>\nAmazon<\/td>\n<\/tr>\n
Job Role<\/strong><\/td>\nApplied Scientist, Prime Video Commerce Insights<\/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 Prime Video Commerce Insights, where the focus is on using machine learning to improve how customers discover, subscribe to, and engage with video content. The team\u00e2\u0080\u0099s mission is to make sure the right offer reaches the right customer at the right moment across subscriptions, channels, and transactional video, while replacing static business rules with data-driven decisions that personalise the full commerce journey. The work is carried out at Amazon scale, serving hundreds of millions of customers and exploring newer approaches such as agentic and generative AI, behavioural simulation, and causal inference to understand the effect of decisions before they are shown to customers.<\/p>\n

This is a hands-on applied science position for someone with strong reinforcement learning expertise and broad machine learning capability. You will work on customer-facing models, study customer behaviour at scale, and help develop scalable personalisation systems that improve decision-making across Prime Video Commerce. The role is based in London and is part of a high-performing, highly visible multidisciplinary group of scientists and engineers. The work combines rigorous research with practical delivery, and the models you build are expected to move into production and influence real customer and business outcomes.<\/p>\n

What you will do<\/h3>\n
    \n
  • Apply reinforcement learning and related machine learning techniques to build personalised recommendation and decision systems across the customer journey.<\/li>\n
  • Research, design, and implement models that adapt the experience at different customer touchpoints.<\/li>\n
  • Partner with engineers to move successful experiments into Amazon\u00e2\u0080\u0099s large-scale production environment while meeting strict latency requirements.<\/li>\n
  • Build models that can process very large volumes of data and support recommendations for customers globally.<\/li>\n
  • Design and run experiments with scientific discipline so that results clearly demonstrate both technical effectiveness and business value.<\/li>\n
  • Provide technical leadership on machine learning methods and help guide the team\u00e2\u0080\u0099s science roadmap and research agenda.<\/li>\n
  • Work with technical product managers to identify customer priorities and turn them into model-based solutions.<\/li>\n
  • Share results with the team and the wider scientific community through clear, rigorous, and business-relevant written work.<\/li>\n
  • Collaborate with engineers and scientists to solve complex, ambiguous problems that affect Prime Video and other Amazon businesses.<\/li>\n
  • Contribute to systems that balance multiple objectives, including customer experience and commercial performance, at very large scale.<\/li>\n<\/ul>\n

    What the team environment is like<\/h3>\n

    You will join a group of engineers and applied scientists known for solving difficult, ambiguous problems and for producing patents and publications in respected venues. The team has direct visibility with senior Prime Video leadership and works across Commerce, Content, and Platform organisations to influence how customers find, subscribe to, and use video content. It is a setting where research is expected to translate into production systems, and where ideas can move quickly from concept to real-world impact.<\/p>\n

    What Amazon is looking for<\/h3>\n
      \n
    • Deep experience with reinforcement learning.<\/li>\n
    • Evidence of research output, such as patents or publications in top-tier peer-reviewed conferences or journals.<\/li>\n
    • Programming ability in Java, C++, Python, or a similar language.<\/li>\n
    • Experience in at least one relevant technical area such as algorithms and data structures, parsing, numerical optimisation, data mining, parallel and distributed computing, or high-performance computing.<\/li>\n
    • Experience building machine learning models for business use.<\/li>\n
    • Ability to think strategically about business, product, and technical challenges and to communicate effectively with both technical and business audiences.<\/li>\n
    • Strong collaboration and communication skills.<\/li>\n
    • A customer-first mindset and the ability to work backwards from customer needs.<\/li>\n
    • Comfort working in a fast-moving environment with complex, high-impact problems.<\/li>\n
    • Preferred experience with Unix\/Linux.<\/li>\n
    • Preferred experience in professional software development.<\/li>\n<\/ul>\n

      Additional information<\/h3>\n

      Amazon describes itself as an equal opportunities employer and says that hiring decisions are based on experience and skills. The company also states that it values a diverse workforce and an inclusive culture. If you need a workplace adjustment or accommodation during the application, interview, or onboarding process, support is available through Amazon\u00e2\u0080\u0099s accommodations process.<\/p>\n

      The posting also includes Amazon\u00e2\u0080\u0099s privacy notice and legal information, along with links for candidate support and hiring resources.<\/p>\n\n

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

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