LLM & Conversational AI Data Scientist II

Amazon.com, Inc.

Greater London

On-site

GBP 70,000 - 110,000

Full time

3 days ago
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Job summary

Amazon Development Centre (London) Limited is seeking a Data Scientist to advance LLM-powered conversational experiences for Rufus, our AI-driven shopping assistant. You will design, evaluate, and iterate instructions and evaluation pipelines, leveraging retrieval augmentation and context enrichment to improve response quality and customer impact.

The role involves developing scalable metrics, dashboards, and experiments, and collaborating with Applied Scientists and Engineers to translate

Qualifications

  • Experience with machine learning/statistical modeling data analysis tools and techniques.
  • Experience in a ML or data scientist role with a large technology company.
  • 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.
  • Master's degree or above in Math, Statistics, Computer Science, or related science field.

Responsibilities

  • Develop and maintain LLM instruction iterations and evaluation frameworks.
  • Collaborate with cross-functional teams to experiment with retrieval augmentation and context enrichment.
  • Design and analyze A/B tests and experiments to evaluate model improvements.
  • Develop metrics, dashboards, and reporting frameworks to monitor system performance and business impact.
  • Translate analytical insights into production systems with model evaluation and deployment.

Skills

Machine learning
Statistical modeling
Communication

Education

Master's degree or above in Math, Statistics, Computer Science, or related field

Tools

SQL
Python
R

Job description

Amazon Development Centre (London) Limited is seeking a Data Scientist to advance LLM-powered conversational experiences for Rufus, our AI-driven shopping assistant. You will design, evaluate, and iterate instructions and evaluation pipelines, leveraging retrieval augmentation and context enrichment to improve response quality and customer impact.

The role involves developing scalable metrics, dashboards, and experiments, and collaborating with Applied Scientists and Engineers to translate

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