Applied Scientist , Customer Experience and Business Trends
Amazon is hiring an Applied Scientist , Customer Experience and Business Trends in Seattle, United States. It pays $143k-$193k a year and Level rates it ; you can apply on Level.
AI in this role
As part of CXBT, we have a vision to revolutionize how we understand, test, and optimize customer experiences at scale. Where traditional testing approaches fall short, we create AI-powered solutions that enable rapid experimentation, de-risk product launches, and generate actionable insights, all before a single real customer is impacted.
Be a part of our agentic initiative and shape how Amazon leverages artificial intelligence to run tests at scale and improve customer experience.
As an applied scientist, you will research state-of-the-art techniques in agent-based modeling, and lead scientific innovation building foundational agentic simulation capabilities.
If you are passionate about the intersection of AI and human behavior modeling, and want to fundamentally influence how Amazon tests and improves customer experiences, this role offers a great opportunity to make your mark.
Key job responsibilities
- Design and implement frameworks for multi-modal content handling and creating representative, diverse agents that faithfully capture real-world characteristics
- Use state-of-the-art techniques in user modeling and behavioral simulation to build robust agentic frameworks
- Research and implement novel algorithms and modeling techniques.
- Acquire and curate diverse datasets while ensuring user privacy.
- Create robust evaluation metrics and test sets to assess language model performance.
- Innovate in data representation and model training techniques.
- Apply responsible AI practices throughout the development process.
- Write clear, scientific documentation describing methodologies, solutions, and design choices
A day in the life
Our team is dedicated to improving Amazon's products and services through evaluation of the end-to-end customer experience using both internal and external processes and technology. Our mission is to deeply understand our customers' experiences, challenge the status quo, and provide insights that drive innovation to improve that experience. Through our analysis and insights, we inform business decisions that directly impact customer experience as customers of new GenAI and LLM technologies.
About the team
CXBT is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings – for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers).
Basic qualifications
- 3+ years of building models for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- PhD or equivalent research experience
- Experience building machine learning models or developing algorithms for business application
Preferred qualifications
- Have publications at top-tier peer-reviewed conferences or journals
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Deep expertise in multimodal AI systems combining vision and language models and designing and building LLM-based agent systems
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
How we rate this
Applied Scientist , Customer Experience and Business Trends at Amazon rates 92 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in applied scientist jobs at this level
Pay
- This job starts at
- $143k
- Typical applied scientist job
- $167k
This posting starts 15% below the typical applied scientist job. See applied scientist jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you think about the risk of an AI system in this kind of role failing silently?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI agents and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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