Data Scientist II, Alexa for Shopping Science UK
Amazon Development Centre (London) Limited•2h ago
United KingdomOnsiteFull-timeMid Level2+ yrs exp
Top focus
Data ScientistVp DataData Analyst
- We are looking for a passionate, talented
- inventive Data Scientist with a strong machine learning and analytics background to help build industry-leading language technology powering Alexa for Shopping, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey. This innovative role focuses on developing conversation-based, multimodal shopping experiences, utilizing data analysis, statistical modeling, machine learning (ML) technologies
- experimentation to drive product decisions and optimize customer experiences. Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration
- more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference
- data-driven insights to continuously improve our systems. Key job responsibilities Key job responsibilities As a Data Scientist on our team, you will be responsible for the analysis, modeling
- 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
- product partners locally and abroad. Your work will include designing experiments, analyzing results
- launching new features, products and systems. A day in the life 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
- 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
- reporting frameworks to monitor system performance, customer engagement
- business impact. Build predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience, conversion
- 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
- experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports
- data visualizations. About the team 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, enabling customers to set price alerts or empower AfS 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
- Data Mining. We validate our work by actively participating in the internal and external scientific communities.
- Master's degree or above in Math, Statistics, Computer Science
- 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
- parameters that affect their performance - Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS
- 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
- EC2 - Experience working on multi-team, cross-disciplinary projects Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability
- other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Required skills
Machine LearningData AnalysisStatistical ModelingNatural Language ProcessingA/B TestingData MiningSQLPythonAWSS3RedshiftSagemakerEMRKinesisLambda