Research Scientist, Talent Assessment

Job description

DESCRIPTION

Amazon's Talent Assessment team designs and implements groundbreaking hiring solutions for one of the world's fastest growing companies. We work in a fast-paced, global environment where we must solve complex problems (ranging from research-based to technical) and deliver solutions that have impact.

We are seeking personnel selection researchers with a strong foundation in the development of pre-hire selection assessments, traditional and alternative legally defensible assessment validation approaches, research methodology, and data analysis. Preferred candidates will have a experience in applying new methodologies and technology such as machine learning and natural language processing. We are looking for equal parts researchers and consultant/thought leaders who are highly adaptable and continual learners who thrive in a fast paced environment.
You will work closely with global teams to design and experiment new hiring solutions that predict success for highly complex roles (technical and non-technical) that have great impact on Amazon globally (for example, AWS, Kindle, Retail, and Business & Development).

What you'll do:
· Lead the tactical development and execution of large scale, highly visible personnel selection research projects
· Develop and iterate on experimental research studies to optimize qualitative and quantitative hiring strategies
· Develop and innovate on new pre-hire test assessment design, validation, and implementation
· Partner with internal and external technology teams
· Influence executive project sponsors and multiple business and development teams across the company
· Drive effective teamwork, communication, and collaboration across multiple stakeholder groups

Desired profile

BASIC QUALIFICATIONS

· Master's degree in Industrial-Organizational Psychology or related field
· 3 years of relevant experience in applied selection practices, job analysis, test development, and validation
· Foundational skills in conducting experimental research studies and data analysis
· Proficiency in at least one statistics program (SPSS, R, SAS, etc.)