Amazon
Data Scientist II, Alexa for Shopping Science UK, Alexa for Shopping Science UK
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Data Scientist II, Alexa for Shopping Science UK, Alexa for Shopping Science UK
Data Scientist – Alexa for Shopping (Conversational Shopping AI)
We are seeking a passionate, talented, and 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. Our goal is to simplify the shopping journey for customers by enabling seamless product discovery, comparisons, recommendations, and visual search-based transactions.
About the Role
This critical role focuses on developing conversation-based, multimodal shopping experiences using data analysis, statistical modeling, machine learning (ML), and experimentation to drive product decisions and optimize customer experiences.
Our Mission
We empower customers to find and discover products tailored to their needs through:
- Product research and comparison support
- Direct shopping via images or videos
- Visual inspiration and personalized recommendations
- Advanced AI-driven conversational and multimodal systems
We achieve this by leveraging:
- Advanced analytics
- Natural Language Processing (NLP)
- Machine Learning (ML)
- A/B testing and causal inference
- Data-driven insights
Key Responsibilities
As a Data Scientist on our team, you will:
- Develop and optimize AI technologies that shape the future of multimodal conversational shopping systems, including:
- Large language models (LLMs)
- Information retrieval
- Recommender systems and knowledge graphs
- Handle Amazon-scale use cases with a significant impact on customer experiences.
- Lead the design, execution, and analysis of experiments, A/B tests, and feature evaluations.
- Collaborate closely with Applied Scientists, Engineers, and Product teams—both locally and internationally.
- Translate data insights into actionable strategies, driving continuous system improvements.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Daily Work Examples
- Perform hands-on analysis of large-scale multimodal datasets to derive actionable insights.
- Apply statistical methods, ML, and data mining to optimize conversational shopping assistants, leveraging both structured and unstructured contextual signals.
- Design, launch, and analyze A/B tests to refine system performance, ensuring statistical rigor and impactful outcomes.
- Develop metrics, dashboards, and reporting frameworks for monitoring:
- System performance
- Customer engagement
- Business outcomes (conversion, satisfaction, etc.)
- Build predictive models to identify opportunities for personalization, recommendation enhancement, and conversion lift.
- Work alongside Engineering teams to deploy models, refining metric generation and experimentation pipelines.
- Establish automated data workflows, including:
- ETL pipelines
- Large-scale data ingestion
- Domain-specific ML research tools
- Present findings to stakeholders, both technical and non-technical, using clear communication in presentations, reports, and visualizations.
About the Team
The Alexa for Shopping Science team (based in London) is part of Amazon’s AI-driven shopping assist ecosystem, comprising:
- 150+ engineers, designers, and product leaders
- A cross-functional approach integrating AI advancements into shopping workflows.
Research Focus Areas
Our team advances:
- Agentic AI for automated shopping actions (e.g., price alerts, self-driving purchases)
- Multimodal understanding (handling text, images, audio, and video)
- Generative AI (GenAI) and information retrieval enhancements
- Web and catalog-based research reports for personalized shopping insights
Get help with your application
Your very own career expert that helps elevate your application to the next level.
We engage actively with both internal and external scientific communities to refine our solutions.
Basic Qualifications
- Master’s degree (or equivalent) in:
- Math
- Statistics
- Computer Science
- Related quantitative/technical field
- 2+ years of experience in a Machine Learning/Data Science role, ideally at a large technology company.
- Proven expertise in:
- ML/statistical modeling, including hyperparameter tuning, evaluation metrics, and model performance constraints.
- Data scripting languages (e.g., SQL, Python, R) or statistical tools (e.g., R, SAS, MATLAB).
- Strong ability to communicate complex concepts clearly across technical and non-technical audiences.
Preferred Qualifications
- Experience in:
- Defining and implementing benchmarking frameworks for Generative AI models.
- Working with AWS services, including:
- Storage (S3)
- Data warehousing (Redshift)
- ML/analytics (SageMaker, EMR)
- Real-time processing (Kinesis, Lambda)
- Compute (EC2)
- Background in multi-disciplinary, cross-team projects requiring collaborative ownership of challenges.
Amazon Principles
Amazon is an inclusive workplace committed to:
- Equal opportunity employment for all, including protected veteran status and persons with disabilities.
- Diversity and belonging, valuing insights from all backgrounds.
For our candidates, Amazon prioritizes:
- Personal privacy and data security.
- Reasonable accommodations for interviews and hiring—visit Amazons disAbility hiring resources.
All hiring decisions are based on your skills, qualifications, and passion.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location