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  • Posted: Feb 26, 2026
    Deadline: Not specified
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  • Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are ...
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    Data Scientist II, RufusX Science

    Key job responsibilities

    • Key job responsibilities As a Data Scientist on our team, you will be responsible for the analysis, modeling, and optimization of AI technologies that will shape the future of shopping experiences. You will play a critical role in measuring and improving multimodal conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graphs, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include designing experiments, analyzing results, and launching new features, products and systems.

    A day in the life
    You Will

    • Perform hands-on analysis and modeling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys. Use statistical methods, machine learning, and data mining techniques to create scalable solutions for measuring and optimizing shopping assistant systems based on a rich set of structured and unstructured contextual signals. Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights. Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact. Build predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience, conversion, and satisfaction. Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. Establish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations.

    About The Team

    • The Rufus Features Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the Rufus AI, from making Rufus agentic, enabling customers to set price alerts or empower Rufus to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.

    Basic Qualifications

    • Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
    • Experience in a ML or data scientist role with a large technology company
    • Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
    • Experience effectively communicating complex concepts through written and verbal communication
    • Master's degree or above in Math, Statistics, Computer Science, or related science field

    Preferred Qualifications

    • Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
    • Experience in defining and creating benchmarks for assessing GenAI model performance
    • Experience working on multi-team, cross-disciplinary projects

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    Method of Application

    Interested and qualified? Go to Amazon on www.amazon.jobs to apply

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