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Applied Scientist, Amazon Customer Service

Amazon

Applied Scientist, Amazon Customer Service

full-timePosted: Aug 13, 2026Updated: Aug 27, 2026Seattle, Washington, United States

Job Description

The Data Intelligence team is a new function within Amazon Customer Service (CS). We own the end-to-end process of defining, building, implementing, and monitoring a comprehensive data strategy. We also develop and apply Generative Artificial Intelligence (GenAI), Machine Learning (ML), Ontology, and Natural Language Processing (NLP) to enhance customer service associate and customer experiences. As an Applied Scientist, you'll own the definition and implementation of customer-focused, AI-driven innovation in Amazon Customer Service globally, leveraging GenAI, ML, and/or NLP to transform complex business requirements and customer needs into innovative technology solutions. Your expertise will be key in shaping data-driven strategies and addressing complex data challenges. With your expertise in AI, text analysis, embeddings, language modeling, and generation, you'll design and develop scalable AI-powered technology solutions, prioritize initiatives, drive data-driven insights, and deliver business impact. This position will advance applied science best practices, leverage data and AI to drive customer experience improvements, and set new global standards for customer experience. This role requires you to work with a cross-functional team, including scientists, engineers, and product managers, to develop scalable and maintainable AI solutions for both structured and unstructured data. The ideal candidate has strong technical skills in AI techniques (e.g., automated reasoning, reasoning, planning, knowledge representation), excellent written documentation skills, and experience with big data technologies. Success in this role requires combining deep business knowledge with hands-on technical skills to solve customer problems and address complex technical challenges. Key job responsibilities - Develop innovative solutions to complex problems (e.g., Automated Reasoning for Trusted AI-Enabled Customer Service). - Apply technical expertise to implement novel algorithms and modeling solutions, in collaboration with other scientists and engineers. - Analyze data and define metrics to identify actionable insights and measure improvements in customer experience. - Communicate results and insights to both technical and non-technical audiences through written reports, presentations, and internal/external publications. - Collaborate with product management and engineering teams to integrate and optimize models in production systems. A day in the life A typical day as an Applied Scientist in the Data Intelligence team involves combining business expertise with hands-on problem-solving in ML and AI. The role encompasses tackling complex data initiatives, ensuring alignment with customer needs and business objectives, and translating business requirements into practical AI-driven solutions. Working collaboratively with cross-functional teams, this position involves designing and enhancing AI models, focusing on efficiency, precision, and scalability. Daily activities include ensuring data quality, monitoring model performance, and generating actionable insights from vast amounts of information. Each day presents opportunities to resolve complex technical challenges, advance important AI projects, and conceive innovative ways to leverage data in transforming the customer experience. About the team The Data Intelligence team is a new function within Amazon Customer Service. We develop and apply Generative Artificial Intelligence (GenAI), Machine Learning (ML), and Natural Language Processing (NLP) techniques to enhance customer service associate and customer experiences.

Locations

  • Seattle, Washington, United States
  • Santa Clara, California, United States

Salary

171,600 - 222,200 USD / yearly

Skills Required

  • patentsintermediate
  • any of the following areas: algorithmsintermediate
  • Unix/Linuxintermediate
  • professional software developmentintermediate

Required Qualifications

  • 3+ years of building models for business application experience (experience, 3 years)
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience (experience, 4 years)
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals (experience)
  • Experience programming in Java, C++, Python or related language (experience)
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing (experience)

Preferred Qualifications

  • Experience using Unix/Linux (experience)
  • Experience in professional software development (experience)
  • Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. (experience)

Responsibilities

  • Develop innovative solutions to complex problems (e.g., Automated Reasoning for Trusted AI-Enabled Customer Service).
  • Apply technical expertise to implement novel algorithms and modeling solutions, in collaboration with other scientists and engineers.
  • Analyze data and define metrics to identify actionable insights and measure improvements in customer experience.
  • Communicate results and insights to both technical and non-technical audiences through written reports, presentations, and internal/external publications.
  • Collaborate with product management and engineering teams to integrate and optimize models in production systems.

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