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 powerful 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, Global Hiring Science owns and develops products and services using Artificial Intelligence and Machine Learning that enhance recruitment. We collaborate with scientists to build and maintain machine learning solutions for hiring, offering opportunities to both apply and develop ML engineering skills in a production environment.
In this role, you'll have the opportunity to spearhead voice of customer workstreams that measure, understand, and improve hiring experiences for candidates, hiring managers, interviewers, and beyond. We're seeking a scientific leader with expertise in survey methodologies, psychometrics, experimental design, and advanced statistical analysis. In this role, you'll:
• Lead the development and implementation of sophisticated survey methodologies to capture critical insights across Amazon's corporate hiring domains.
• Apply your expertise in psychometrics to ensure the validity and reliability of our measurement instruments.
• Utilize advanced statistical techniques to analyze complex datasets, analyze open text feedback, uncover meaningful patterns, and derive actionable insights.
• Design and conduct experiments to test new measurement methods and improve the precision of our customer experience metrics.
• Collaborate with cross-functional teams to translate scientific findings into practical solutions that enhance the hiring process.
As a science lead, you'll be at the forefront of reinventing how we understand and improve the hiring experience for all involved. You'll work with state-of-the-art research tools, leveraging AI and machine learning algorithms to solve complex challenges in survey methodology and data analysis.
Your work will directly contribute to Amazon's ability to fairly and precisely connect the right people to the right jobs, impacting millions of candidates and employees worldwide.
Key job responsibilities
What you’ll do as a GHS Research Scientist:
• Develop and execute content development and validation strategies to drive more effective decisions and improve the experiences across customer groups
• Conduct psychometric analyses to evaluate integrity and practical application of survey questions and data
• Apply advanced statistical techniques to analyze massive, diverse datasets to uncover insights that optimize our customer experience and drive hiring excellence
• Explore emerging technologies and innovative methodologies to enhance experience 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, including senior business leaders
• Ensure effective teamwork, communication, collaboration, and commitment across multiple teams with competing priorities
• Manage full life cycle of research programs (develop strategy, gather requirements, manage and execute)
