Applied Scientist, People eXperience & Technology Central Science (PXTCS)

Amazon Science
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Job Description

Are you motivated to explore research in ambitious and ambiguous spaces? Are you interested in conducting research that will improve the employee and manager experience at Amazon? Do you want to work on an interdisciplinary team of scientists that collaborate rather than compete? Join us at PXT Central Science!

The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.

We are seeking an Applied Scientist with expertise in more than one or more of the following areas: machine learning, natural language processing, computational linguistics, algorithmic fairness, reinforcement learning, Bayesian methods, predictive analytics, decision theory, recommender systems, and deep learning. In this role, you will lead and support research efforts within all aspects of the employee lifecycle: from candidate identification to recruiting, to onboarding and talent management, to leadership and development, to finally retention and brand advocacy upon exit.

The ideal candidate should have strong problem-solving skills, excellent business acumen, the ability to work independently and collaboratively, and have an expertise in both science and engineering. The ideal candidate is not methods-driven, but driven by the research question at hand; in other words, they will select the appropriate method for the problem, rather than searching for questions to answer with a preferred method. The candidate will need to navigate complex and ambiguous business challenges by asking the right questions, understanding what methodologies to employ, and communicating results to multiple audiences (e.g., technical peers, functional teams, business leaders).

Key job responsibilities

Applied Scientists in PXTCS work with customers and partner teams to understand user pain points, formulate the science problem, science strategy, and success metrics, work with as well as expand rich data sources, create proofs of concept to validate assumptions and get feedback, and integrate with live platforms for another round of feedback. Applied Scientists collaborate with other scientists and publish their research in top tier conferences.

About the team

We are a collegial and multidisciplinary team of researchers in People eXperience and Technology (PXT) that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. We leverage data and rigorous analysis to help Amazon attract, retain, and develop one of the world’s largest and most talented workforces.


  • PhD in Computer Science, Electrical Engineering, Computational Linguistics, Natural Language Processing, or related fields
  • Skilled in Python or similar programming languages
  • Knowledge and practical experience in more than one of the following areas: machine learning, natural language processing, semantic parsing, statistical inference, causal modeling, reinforcement learning, Bayesian methods, predictive analytics, decision theory, recommender systems, deep learning
  • Demonstrated use of modeling and optimization techniques tailored to meet business needs.
  • Track record of solving ambiguous problems and delivering complex ML solutions to customers
  • Excellent technical writing and communication skills and ability to convey scientific concepts to non-technical business audiences
  • Highly adaptable, creative, and thrives in a fast-paced work environment
  • Track record of publishing in premier journals and conferences in the above areas


  • Deep experience in several of the above areas and experience with frameworks such as PyTorch/Tensorflow
  • Created production systems; 2+ years of experience deploying solutions to AWS and/or hosting and maintaining AWS based production systems
  • Knowledge of software engineering best practices for the full software development life cycle (i.e., coding standards, code reviews, source control management, build processes, and testing)
  • Familiarity with AWS and knowledge of distributed computing
  • Experience with fact extraction, entity linking, question answering, semantic parsing, natural language generation, ontologies and knowledge representation - particularly for question answering.

Company Info.

Amazon Science

Amazon Science examines the company’s approach to scientific innovation. Amazon believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields.

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