Quantitative UX Researcher, Applied AI Solutions
Amazon - Seattle, Washington, USA
Posted Apr 1, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
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- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
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About this role
Quantitative UX Researcher, Applied AI Solutions Seattle, Washington, USA We are seeking a Quantitative UX Researcher who is excited to help shape the future of AI-native business applications. This is an opportunity to influence product direction by helping teams understand how customers interact with AI-powered experiences and what drives adoption, trust, usability, and customer value. In this role, you will lead quantitative research that helps teams build, test, and learn faster. You will turn product questions into clear hypotheses, success metrics, well-designed studies, and actionable insights. Your work will help teams evaluate new ideas, improve existing experiences, and make better product decisions. This is a quant-first role with mixed-methods responsibilities as needed. We are looking for a researcher with strong skills in experimentation, analytics, behavioral analysis, and causal inference. You should be comfortable working in ambiguous, early-stage spaces and helping teams define how success should be measured for new AI-powered products. You will identify meaningful behavioral and attitudinal signals, measure product performance, and recommend improvements based on the evidence. Key job responsibilities - Lead quantitative and mixed-methods research for AI-powered products, including early-stage concepts and evolving customer experiences. - Own studies from end to end, including framing research questions, defining hypotheses, selecting methods, identifying measures, analyzing results, and communicating recommendations. - Design and run experiments, surveys, and behavioral analyses that help teams understand customer needs, product performance, and opportunities for improvement. - Define and track success metrics related to adoption, trust, usability, comprehension, and customer value in AI-powered experiences. -
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