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Senior Research Scientist, Experience Analytics
Amazon
On-siteseniorPosted May 5, 2026
About the Role
Lead customer perspectives research, apply rigorous statistical methods to customer experience data, develop research frameworks for emerging customer populations, and inform product strategy.
Requirements
Requires strong statistical depth, experience with behavioral data, causal inference, and ability to design research studies and frameworks to understand customer behavior.
Full Job Description
AWS Experience Analytics (EXA) is seeking a Research Scientist to lead customer perspectives research for the team. EXA exists to turn customer understanding into products and intelligence that teams across AWS can use. We run customer experience deep dives, product futures research, and forward-looking studies that bring decision-makers face-to-face with how customers experience AWS. The research this team produces shapes product strategy, investment decisions, and how AWS leadership thinks about the customer.
What we need is someone who thinks like a scientist about customers. You have the statistical depth to work with complex behavioral data — building models, testing hypotheses, finding structure in messy signals — and the instinct to go beyond the data when the data is not enough. You are not satisfied with a model that predicts behavior without understanding why.
The landscape is shifting. AWS customers are moving from traditional console-based building toward AI-augmented, agent-primary, and autonomous workflows. Understanding who these customers are, how they think, and what they need requires new research approaches — not just new data. You will design the studies, develop the frameworks, and produce the evidence that helps AWS see its customers clearly as this transformation unfolds.
You will work alongside data scientists, applied scientists, engineers, and research teams who are building the data foundations for customer understanding.
Key job responsibilities
- Apply rigorous statistical methods to customer experience data — segmentation analysis, behavioral pattern analysis, causal inference, and outcome measurement — grounded in the team's customer lifecycle data and metrics frameworks.
- Produce research findings structured to inform product strategy and leadership decisions.
- Develop research frameworks and approaches for understanding emerging customer populations — AI-augmented builders, agent-primary developers, Gen Z digital natives — where existing methods may not apply.
- Write compelling, clear research narratives for technical and non-technical audiences, including senior leadership.
- Contribute to the team's scientific direction and mentor others.
About the team
Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, has not followed a traditional path, or includes alternative experiences, do not let it stop you from applying.
Mentorship and Career Growth We are continuously raising our performance bar as we strive to become Earth's Best Employer. That is why you will find endless knowledge-sharing, mentorship, and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there is nothing we cannot achieve in the cloud.
What we need is someone who thinks like a scientist about customers. You have the statistical depth to work with complex behavioral data — building models, testing hypotheses, finding structure in messy signals — and the instinct to go beyond the data when the data is not enough. You are not satisfied with a model that predicts behavior without understanding why.
The landscape is shifting. AWS customers are moving from traditional console-based building toward AI-augmented, agent-primary, and autonomous workflows. Understanding who these customers are, how they think, and what they need requires new research approaches — not just new data. You will design the studies, develop the frameworks, and produce the evidence that helps AWS see its customers clearly as this transformation unfolds.
You will work alongside data scientists, applied scientists, engineers, and research teams who are building the data foundations for customer understanding.
Key job responsibilities
- Apply rigorous statistical methods to customer experience data — segmentation analysis, behavioral pattern analysis, causal inference, and outcome measurement — grounded in the team's customer lifecycle data and metrics frameworks.
- Produce research findings structured to inform product strategy and leadership decisions.
- Develop research frameworks and approaches for understanding emerging customer populations — AI-augmented builders, agent-primary developers, Gen Z digital natives — where existing methods may not apply.
- Write compelling, clear research narratives for technical and non-technical audiences, including senior leadership.
- Contribute to the team's scientific direction and mentor others.
About the team
Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, has not followed a traditional path, or includes alternative experiences, do not let it stop you from applying.
Mentorship and Career Growth We are continuously raising our performance bar as we strive to become Earth's Best Employer. That is why you will find endless knowledge-sharing, mentorship, and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there is nothing we cannot achieve in the cloud.