Data Scientist II, Alexa for Shopping Science UK

Job ID: Amazon Development Centre (London) Limited

We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to build industry leading language technology powering Alexa for Shopping, an AI driven search and shopping assistant that helps customers at every step of their shopping journey.

As a Data Scientist on our team, you will be responsible for the analysis, modeling, and optimization of AI technologies that shape the future of shopping experiences. You will play a critical role in measuring and improving multimodal conversational systems-especially 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 customers' experiences and 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.

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.

The Alexa for Shopping 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 AfS AI-from making it agentic and enabling customers to set price alerts or automatically purchase items at the right price, 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 personalized shopping guidance. We utilize and advance state of the art techniques in NLP, generative AI, information retrieval, machine/deep learning, and data mining. We validate our work by actively participating in internal and external scientific communities.

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

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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.