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# Data Scientist, AWS Quick Data

- **Company:** Amazon.com, Inc.
- **Location:** New York, NY, United States
- **Salary:** $136,000.0 - $207,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Big Data, Data Auditing, Query Languages, R (Programming Language), Python (Programming Language), MATLAB, Machine Learning, Mathematical Software, SAS (Software), SQL Databases, Scripting, Retrieval-Augmented Generation, Large Language Models, Model Validation, Generative AI, AI Platforms, Data Analytics, Virtual Agents, Data Pipelines
- **Published:** May 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f42166ed2eed85bc

## About the Role

Do you have experience in Machine learning/AI-based analysis?, * 2+ years of data scientist experience

 * 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
 * 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
 * 1+ years of working with or evaluating AI systems experience
 * 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
 * Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
 * Experience applying theoretical models in an applied environment, * Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
 * Knowledge of machine learning concepts and their application to reasoning and problem-solving
 * Experience in a ML or data scientist role with a large technology company
 * Experience in defining and creating benchmarks for assessing GenAI model performance
 * Experience working on multi-team, cross-disciplinary projects
 * Experience applying quantitative analysis to solve business problems and making data-driven business decisions
 * Experience effectively communicating complex concepts through written and verbal communication

## Description

Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale., We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale.
As part of our diverse team-including data scientists, engineers, language engineers, linguists, and program managers-you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.

Key job responsibilities
In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions.
Specific responsibilities include:

 * Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features
 * Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings
 * Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases
 * Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance
 * Develop and refine annotation guidelines and quality frameworks for evaluation tasks
 * Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies
 * Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements
 * Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts
 * Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets


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