Do you want a role with deep meaning and the ability to make a major impact? 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. Together, we can solve the world's toughest hiring problems.A day in the lifeAs 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.About the teamThe 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.
Locations
United Kingdom, MLN, Edinburgh, Edinburgh, MLN, United Kingdom
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
140,000 - 220,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- PhD, or a Master's degree and experience in quantitative field researchintermediate
- Knowledge of R or Pythonintermediate
- Experience communicating qualitative research methods and findings to non-qualitative researchersintermediate
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and productsintermediate
- Experience in applied selection research, job analysis, test development, and validationintermediate
Required Qualifications
- PhD, or a Master's degree and experience in quantitative field research (experience)
- Knowledge of R or Python (experience)
- Experience communicating qualitative research methods and findings to non-qualitative researchers (experience)
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products (experience)
- Experience in applied selection research, job analysis, test development, and validation (experience)
Preferred Qualifications
- Experience converting research studies into tangible real-world changes (experience)
- Knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker (experience)
- Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc. (experience)
- PhD in Industrial/Organizational Psychology or related field (degree in industrial)
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