Sr Data Scientist

Description

About Amazon Quick: Amazon Quick is an enterprise AI workspace that brings together intelligent agents, deep research, business intelligence, and workflow automation. It lets employees find answers across their company's data, apps, and the web, turn insights into action, and automate repetitive work. Organizations of every size rely on Quick to make faster, better-informed decisions with AI they can trust.

About the Team: The Quick Data team builds the high-quality datasets that power and measure Amazon Quick. Our work spans human evaluation, Responsible AI safeguards, Retrieval-Augmented Generation (RAG), and benchmarking. It makes sure Quick's generative AI features are enterprise-ready, safe, and effective at scale. The team includes data scientists, engineers, language engineers, linguists, and program managers who partner closely with science, engineering, and product teams. Customer obsession and high standards drive everything the team delivers.

About the Role: The Quick Data team is hiring a Data Scientist II to lead evaluation and benchmarking data development for Quick features. In this role, you will design the datasets, metrics, and evaluation frameworks that show whether Quick meets customer needs. Your insights will shape product direction and model improvements.

Key job responsibilities

• Design and build evaluation and benchmark datasets
• Define quality metrics and evaluation frameworks, including human evaluation, model-based evaluation (LLM-as-a-Judge), and checks on how well the two correlate
• Run human annotation programs from start to finish: write guidelines, measure inter-annotator agreement, and control data quality
• Analyze model and agent performance to find gaps, root causes, and the highest-impact improvements
• Partner with science, engineering, and product teams to turn evaluation results into launch decisions and roadmap priorities
• Present findings and recommendations to senior leadership

Basic Qualifications

• 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
• 4+ years of data scientist experience
• Experience as a leader and mentor on a data science team

Preferred Qualifications

• 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
• Experience managing data pipelines
• Experience evaluating LLMs, RAG systems, or agentic AI applications