At a Glance
- Tasks: Revolutionise hiring with AI-driven solutions and advanced research strategies.
- Company: Join Amazon's Intelligent Talent Acquisition team, a leader in people science and technology.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make a meaningful impact on people's lives through innovative talent acquisition solutions.
- Qualifications: Master's or PhD in a quantitative field with experience in applied selection research.
- Other info: Collaborate with diverse teams in a dynamic environment focused on solving complex hiring challenges.
The predicted salary is between 36000 - 60000 £ per year.
Do you want a role with deep meaning and the ability to make a major impact? As part of Intelligent Talent Acquisition (ITA), you will 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 will 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 life: 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 will 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 team: 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.
BASIC QUALIFICATIONS
- 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)
PREFERRED QUALIFICATIONS
- 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
- Experience developing and maintaining global hiring assessments
- Strong consulting skills and a track record of influencing stakeholders
- Experience conducting experimental research studies in an industry environment
Senior Research Scientist, Intelligent Talent Acquisition - Lead Generation & Detection Services employer: Amazon Development Centre (Scotland) Limited
Contact Detail:
Amazon Development Centre (Scotland) Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Research Scientist, Intelligent Talent Acquisition - Lead Generation & Detection Services
✨Tip Number 1
Network like a pro! Reach out to current employees at Amazon or in the Intelligent Talent Acquisition space. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Prepare for those interviews by diving deep into AI and machine learning concepts. Brush up on your knowledge of job-person matching and automated evaluation tools. We want to show that we’re not just familiar, but passionate about the tech that drives talent acquisition.
✨Tip Number 3
Don’t forget to showcase our research experience! Bring examples of past projects where we’ve applied scientific principles to solve real-world problems. This is our chance to shine and demonstrate how we can contribute to Amazon’s mission.
✨Tip Number 4
Apply through our website! It’s the best way to ensure our application gets seen. Plus, it shows we’re serious about joining the team and ready to make an impact in the hiring landscape.
We think you need these skills to ace Senior Research Scientist, Intelligent Talent Acquisition - Lead Generation & Detection Services
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior Research Scientist. Highlight your experience in quantitative research and any relevant projects that showcase your skills in AI and machine learning. We want to see how your background aligns with our mission at ITA!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about transforming the hiring process and how your expertise can contribute to our team. Keep it engaging and make sure to connect your experiences to the job description.
Showcase Your Technical Skills: Don’t forget to highlight your proficiency in scripting for data analysis, especially in R or Python. We’re looking for someone who can dive into complex data sets, so be sure to mention any relevant tools or technologies you’ve used in your previous roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensure it gets the attention it deserves. Plus, you’ll find all the details you need about the role there!
How to prepare for a job interview at Amazon Development Centre (Scotland) Limited
✨Know Your Stuff
Make sure you brush up on the latest trends in AI, machine learning, and talent acquisition. Familiarise yourself with Amazon's tech stack and how it applies to the role. Being able to discuss specific projects or research you've done that relates to job analysis or candidate evaluation will show you're not just a fit on paper.
✨Showcase Your Collaboration Skills
Since this role involves working with diverse teams, be ready to share examples of how you've successfully collaborated with others in the past. Highlight any cross-functional projects you've been part of and how you contributed to solving complex problems together.
✨Prepare for Technical Questions
Expect to dive deep into your technical expertise, especially around data analysis and scripting in R or Python. Brush up on your experimental research methods and be prepared to discuss how you've applied these skills in real-world scenarios.
✨Communicate Clearly
Strong communication skills are key, so practice articulating your thoughts clearly and concisely. Whether it's discussing your research findings or explaining complex concepts, being able to convey your ideas effectively will set you apart from other candidates.