Data Scientist II, Alexa for Shopping Science UK

Data Scientist II, Alexa for Shopping Science UK Overview

This role is for a data scientist focused on Alexa for Shopping, Amazon’s AI-powered shopping assistant. The position is centered in London and sits within a team building language technology and analytics capabilities that help customers complete shopping tasks at every stage of their journey. The work combines data analysis, statistical modeling, machine learning, experimentation, and product-focused measurement to improve conversation-based and multimodal shopping experiences.

The team’s mission is to make shopping easier and more useful by helping customers research products, compare options, receive recommendations, get answers to product questions, shop from images or videos, and find visual inspiration. To support that mission, the role uses advanced analytics, natural language processing, machine learning, A/B testing, causal inference, and other data-driven methods to continuously improve the system.

What you will do

• Investigate very large multimodal datasets to understand how customers interact with the shopping assistant and where the experience can be improved.
• Apply statistical techniques, machine learning, and data mining to build scalable measurement and optimization solutions for conversational shopping systems.
• Plan, execute, and evaluate experiments and A/B tests to assess new features and model changes, making sure the results are statistically sound and useful for decision-making.
• Develop monitoring metrics, dashboards, and reporting structures that show system performance, customer engagement, and business impact.
• Create predictive models and carry out detailed analyses to find opportunities to improve customer satisfaction, conversion, and overall experience.
• Partner with Applied Scientists and Engineers to move analytical findings into production, including support for model evaluation and deployment.
• Build automated pipelines and processes for large-scale data analysis, ETL, metric generation, and experimentation workflows.
• Share insights with both technical and non-technical audiences through presentations, written documentation, and data visualizations.
• Help measure and improve multimodal conversational systems, especially those built on large language models, retrieval systems, recommender systems, and knowledge graphs.
• Work with colleagues across science, engineering, and product teams in different locations to design experiments, interpret outcomes, and launch new products and features.

Team context

The Alexa for Shopping Science team in London works with roughly 150 engineers, designers, and product managers. The group helps shape the future of AI-driven shopping at Amazon and contributes to many parts of the Alexa for Shopping experience.

The team is working on making the assistant more agentic, including capabilities such as setting price alerts and allowing the assistant to act on a customer’s behalf to buy products automatically when conditions are right. The team also works on understanding multimodal queries and generating answers that combine text, images, audio, and video. In addition, the group develops deep research-style outputs that search the web and the Amazon catalog to provide detailed, personalized shopping guidance.

The science team uses and advances modern approaches in natural language processing, generative AI, information retrieval, machine learning, deep learning, and data mining. The team also validates its work by taking part in internal and external scientific communities.

What the employer is looking for

• A master’s degree or higher in mathematics, statistics, computer science, or a related scientific field.
• Experience in a machine learning or data science role at a large technology company.
• Experience with machine learning or statistical modeling, data analysis tools and techniques, and the factors that influence model performance.
• Experience using scripting languages for data work, such as SQL, Python, or R, or statistical and mathematical software such as R, SAS, or Matlab.
• Strong written and verbal communication skills, with the ability to explain complex ideas clearly.
• Preferred: experience creating benchmarks to evaluate generative AI model performance.
• Preferred: experience with AWS services including S3, Redshift, SageMaker, EMR, Kinesis, Lambda, and EC2.
• Preferred: experience working on projects that involve multiple teams and disciplines.

Additional information

Amazon says it is an equal opportunities employer and emphasizes that a diverse workforce is important to its success. Hiring decisions are based on experience and skills. The company also states that it values passion for discovery, invention, simplification, and building.

Amazon includes a privacy notice explaining how candidate data is collected, used, and transferred. The company also reiterates that it does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

If you need a workplace accommodation or adjustment during the application, interview, or onboarding process because of a disability, Amazon directs candidates to its accommodations information page. If the country or region you are applying from is not listed, you are asked to contact your recruiting partner.

The page also links to Amazon resources such as benefits information, inclusive experiences, interview tips, leadership principles, working-at-Amazon information, and frequently asked questions.

Degree Requirement: Bachelor’s

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