pymetrics uses innovative measures of soft skills to improve both accuracy and fairness...
pymetrics uses innovative measures of soft skills to improve both accuracy and fairness. Our methodology is patented and based on decades of academic research measuring individual differences in cognitive, social and emotional attributes, or soft skills. Because people are highly complex, a multi-trait assessment of a person is a more accurate picture.
We use best practices in industrial organizational science to link measurement to job-relevance...
We use best practices in industrial organizational science to link measurement to job-relevance. We perform job analyses and local job validation to ensure our models predict success on the job. Additionally, cross-validated profiles are created for each role and company based on those already successful in a given role. This follows best practices of local job validation and concurrent criterion validation.
Every person and role is unique -- and everyone has a fit -- and our job is to facilitate a connection...
Every person and role is unique -- and everyone has a fit -- and our job is to facilitate a connection, not to put people into piles of “winners” and “losers”. No two roles or companies have the same corresponding algorithm so pymetrics can match candidates who aren't a good fit for one role to another where they are.
Founder & Chief Executive Officer
Director of Data Science
Head of Behavioral Science
Computer Science Professor at Northeastern
A third-party audit of the pymetrics model-building process, including a controlled experimental of the de-biasing capability.
Law Professor at Cornell
A comprehensive ethnography of pymetrics as an AI-based hiring assessment, in support of a National Science Foundation grant.
Economics Professor at MIT
A comparative analysis of the prospects for mitigating bias in human decision-makers versus algorithms.