Research Scientist, Talent Acquisition, Global Science

Job  |  Services LLC

Do you want a role with deep meaning and the ability to have a global impact? Hiring top talent is not only critical to Amazon’s success – it can literally change the world. It took a lot of great hires to deliver innovations like AWS, Prime, and Alexa, which make life better for millions of customers around the world. As part of the Intelligent Talent Acquisition (ITA) team, you'll have the opportunity to reinvent Amazon’s hiring process with unprecedented scale, sophistication, and accuracy.

ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals, and more. Our shared goal is to fairly and precisely connect the right people to the right jobs. Last year, we delivered over 6 million online candidate assessments, driving a merit-based hiring approach that gives candidates the opportunity to showcase their true skills. Each year we also help Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of associates in the right quantity, at the right location, at exactly the right time.

You’ll work on state-of-the-art research with advanced software tools, new AI systems, and machine learning algorithms to solve complex hiring challenges. Join ITA in using cutting-edge 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.

Within ITA, the Global Hiring Science (GHS) team designs and implements innovative hiring solutions  work in a fast-paced, global environment where we use research to solve complex problems and build scalable hiring products that deliver measurable impact to our customers. We are seeking selection researchers with a strong foundation in hiring assessment development, legally-defensible validation approaches, research and experimental design, and data analysis.

• Design large-scale personnel selection research that shapes Amazon’s global talent assessment practices across a variety of topics (e.g., assessment validation, measuring post-hire impact)
• Partner with key stakeholders to create innovative solutions that blend scientific rigor with real-world business impact while navigating complex legal and professional standards
• Apply advanced statistical techniques to analyze massive, diverse datasets to uncover insights that optimize our candidate evaluation processes and drive hiring excellence
• Explore emerging technologies and innovative methodologies to enhance talent measurement while maintaining Amazon's commitment to scientific integrity
• Translate complex research findings into compelling, actionable strategies that influence senior leader/business decisions and shape Amazon's talent acquisition roadmap
• Write impactful documents that distill intricate scientific concepts into clear, persuasive communications for diverse audiences, from data scientists to business leaders
• Ensure effective teamwork, communication, collaboration, and commitment across multiple teams with competing priorities

Imagine diving into challenges that impact millions of employees across Amazon's global operations. As a GHS Research Scientist, you'll tackle questions about hiring and organizational effectiveness on a global scale. Your day might begin with analyzing datasets to inform how we attract and select world-class talent. Throughout the day, you'll collaborate with peers in our research community, discussing different research methodologies and sharing innovative approaches to solving unique personnel challenges.

This role offers a blend of focused analytical time and interacting with stakeholders across the globe.

• PhD in a quantitative field, or MS degree and 1+ years of quantitative field research experience
• Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
• Experience with data analysis package (R, SAS, Matlab, etc.)

• PhD in Operations Research, Statistics, Applied Mathematics, Engineering, Computer Science…