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Amazon

Senior Research Scientist, Intelligent Talent Acquisition, Global Hiring Science

Amazon, Seattle, Washington, us, 98127

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Description 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 at scale. We 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.

As a science lead, you'll be at the forefront of reinventing how we understand and improve the hiring experience for all involved. We're looking for an experienced assessment and personnel selection scientist who is equal parts researcher, consultant, and thought leader, with strong expertise in psychometrics, research methodology, and AI application. In this role, you will collaborate with cross-functional teams to drive research, development, and implementation of innovative hiring technology, evaluation tools, approaches, and methods. 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:

Design and execute large-scale, highly-visible global research, validation, and hiring optimization projects.

Solve complex, ambiguous measurement, legal defensibility, and experimental design challenges.

Lead the development and research of new content and AI-based approaches to assessment (e.g., high fidelity simulation, interactive item types, constructed response).

Apply the scientific method to answer novel research questions.

Influence executive project sponsors and stakeholders across the company.

Drive effective teamwork, communication, collaboration, and commitment across cross-functional groups with competing priorities.

Perform complex statistical/quantitative analyses with large datasets.

A day in the life 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.

Basic Qualifications

3+ years of investigating the feasibility of applying scientific principles and concepts to business problems and products experience

PhD, or Master's degree and 5+ years of quantitative field research experience

Preferred Qualifications

PhD in Industrial-Organizational Psychology or related field

5-10+ years of relevant experience in applied selection practices, job analysis, test development, and validation

Strong internal consulting skills and a track record of influencing stakeholders

Proven skills in experimental research design

Experience applying machine learning and artificial intelligence approaches to selection and assessment research

Familiarity with using GenAI tools and Large Language Models (LLMs)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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