Amazon Development Center U.S., Inc.
Technology
Sr.QuantitativeUXResearcher,AppliedAISolutions
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“Sr. Quantitative UX Researcher, Applied AI Solutions at Amazon Development Center U.S., Inc.. Skills: Quantitative UX Research, Applied AI, Experimentation, Causal inference. Lead quantitative research for AI products. Lead mixed-methods research for AI products”
What You'll Achieve.
Define success for new agentic AI products; Create new ways to measure experiences; Define success metrics for agentic AI products; Identify behavioral signals; Identify attitudinal signals; Drive optimizations based on data; Improve how teams learn internally; Scale research impact across organization
Industry & Context.
Turning ambiguous questions into hypotheses; Turning hypotheses into metrics; Turning metrics into studies; Turning studies into evidence
What They're Looking For.
Must Have
Portfolio demonstrating past work, 5+ years leading User Research projects, Knowledge of quantitative approaches, 8+ years data querying languages, 8+ years scripting languages, 8+ years statistical/mathematical software, Experience working with AI systems, Experience with behavioral data collection, Experience with quantitative data analysis, Experience with statistics, Master's degree or equivalent in quantitative field
Nice to Have
Experience creating processes, Experience improving tools, Experience with innovation, Experience with development, Experience with testing, Experience communicating with senior leadership, Experience building machine learning models, Doctorate/PhD or equivalent
What You'll Do.
Lead quantitative research for AI products
Lead mixed-methods research for AI products
Lead research in 0 to 1 spaces
Own experimental design
Select research methods
Translate findings into product actions
Pioneer AI-Native Research Innovation
Set industry standard for AI research
Invent methodologies for AI systems
Adapt methodologies for AI systems
Understand customer interaction with AI
Build trust in AI systems
Triangulate research insights
Craft executive-ready narratives
Drive product improvements
Drive long-term business strategy
Partner with applied science
Partner with engineering
Support build test learn model
Use evidence to shape decisions
Establish Cross-Org Research Standards
Define research frameworks
Define measurement criteria
Define reusable methodologies
Create consistency in research
Raise research bar across AWS AI
How You'll Work.
Team & Collaboration
Partner closely with product; Partner closely with design; Partner closely with applied science; Partner closely with engineering
Communication Scope
Executive Storytelling
Full Job Description
We're seeking a Sr. Quantitative UX Researcher who is passionate about shaping the future of AI-native business applications at scale. This is a rare opportunity to define the research strategy for one of Amazon's next generation of AI-powered solutions — influencing not just product direction, but the broader field of human-AI interaction. As a Sr. Quantitative UX Researcher, you will own experimental design, quantitative analysis, insight generation, and the measurement strategies that turn AI capabilities into meaningful, trustworthy, and human-centered experiences for millions of customers worldwide. You will help teams build, test, and learn faster by turning ambiguous product questions into clear hypotheses, meaningful success metrics, rigorous studies, and decision-ready evidence. Your work will be instrumental to how we evaluate early ideas, improve production experiences, and decide where to invest next. This is a quant-first role, with mixed-methods responsibilities as needed. We are looking for a researcher with deep expertise in experimentation, analytics, behavioral analysis, causal inference, and predictive intelligence. You will work in 0 to 1 environments, define success for new agentic AI products, and create new ways to measure experiences that do not yet have established playbooks. You will define success metrics for agentic AI products, identify the behavioral and attitudinal signals that matter most, and drive optimizations based on what the data shows. You will also invent AI-enabled tools, frameworks, and processes that improve how teams learn internally and scale research impact across the organization. Key job responsibilities - Lead quantitative and mixed-methods research for new and emerging AI products, especially in 0 to 1 spaces where customer needs, product behaviors, and success criteria are still being defined. - Own experimental design from end to end. This includes defining hypotheses, selecting methods, identifying measures, desig
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