Lead Research Scientist

As part of Intelligent Talent Acquisition (ITA), you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy for Amazon Talent Acquisition operations. ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more, all with the shared goal of connecting the right people to the right jobs in a way that is fair and precise. Last year we delivered over 6 million online candidate assessments, and helped Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of workers in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms, leveraging Amazon's in-house tech stack to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. As a Research Scientist, you will partner on design and development of AI-powered systems to scale job analyses enterprise-wide, match potential candidates to the jobs they’ll be most successful in, and conduct validation research for top-of-funnel AI-based evaluation tools. You’ll have the opportunity to develop and implement novel research strategies using the latest technology and to build solutions while experiencing Amazon’s customer-focused culture. The ideal scientist must have the ability to work with diverse groups of people and inter-disciplinary cross-functional teams to solve complex business problems.
The Lead Generation & Detection Services (LEGENDS) organization is a specialized organization focused on developing AI-driven solutions to enable fair and efficient talent acquisition processes across Amazon.
Our work encompasses capabilities across the entire talent acquisition lifecycle, including role creation, recruitment strategy, sourcing, candidate evaluation, and talent deployment. The focus is on utilizing state-of-the-art solutions using Deep Learning, Generative AI, and Large Language Models (LLMs) for recruitment at scale that can support immediate hiring needs as well as longer-term workforce planning for corporate roles.
We maintain a portfolio of capabilities such as job-person matching, person screening, duplicate profile detection, and automated applicant evaluation, as well as a foundational competency capability used throughout Amazon to help standardize the assessment of talent interested in Amazon.
Master's degree, or a PhD and experience in quantitative field research
Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
5+ years of experience in applied selection research, job analysis, test development, and validation
Foundational skills in conducting experimental research studies and data analysis
Proficiency in scripting for data analysis (e.g., R, Python)
Experience in English-language communication skills, both written and verbal
PhD in Industrial/Organizational Psychology or related field
Familiarity with using GenAI tools and Large Language Models (LLMs) in personnel selection research
Strong consulting skills and a track record of influencing stakeholders
Experience conducting experimental research studies in an industry environment
Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice () to know more about how we collect, use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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 for more information. Company - Amazon Development Centre (Scotland) Limited