Cross-functional innovation 

We combine behavioral data and industrial organizational science to push talent acquisition and management beyond the status quo.

Blending behavioral, data, and IO science 

Applying a new science

pymetrics uses tools developed by the global behavioral science community based on decades of research to measure individual differences ...

pymetrics uses tools developed by the global behavioral science community based on decades of research to measure individual differences in cognitive, social and emotional attributes. We measure these traits on an objective scale, rather than through self-reported information. Because people are complex and predicting human behavior is hard, multi-trait assessments create a more accurate representation.

Fit-based system

Imagine if Netflix used Rotten Tomatoes scores to recommend movies to people—everyone would get the same recommendations ...

Imagine if Netflix used Rotten Tomatoes scores to recommend movies to people—everyone would get the same recommendations. This is what traditional tools like IQ tests do. They assume one size fits all and that some people are “better” than others. Instead, Netflix recognizes that each person’s movie tastes are unique. Same with pymetrics. Rather than assuming attributes of a job or person are always good or bad, we recognize that every role and candidate is unique -- and everyone has a fit.

Tailored job-relevance

Finally, we ensure that what we measure is relevant to jobs using industrial organizational science best practices ...

Finally, we ensure that what we measure is relevant to jobs using industrial organizational science best practices. Our job-specific models utilize data collected from strong performers within a specific company. Then we perform job analyses and local job validation to ensure our models predict success on the job.

Backed by research 

A foundation in data science 

pymetrics is the Netflix-like recommendation algorithm for jobs. We build custom, cross-validated profiles for each role and company based on top performers. No two roles or companies have the same algorithm so pymetrics can match candidates who aren't a good fit for one role, to one where they are.

Open source algorithmic auditing 

A diverse workforce is critical for a company’s success, but not all algorithms are objective or fair. If an algorithm is trained on a biased training set, it will simply codify and amplify this bias.

pymetrics has developed an algorithmic auditing tool to identify and remove bias called AuditAI. It provides a framework to highlight any potential biases in an algorithm.

Meet the science team 

Frida Polli, PhD

Founder & Chief Executive Officer

Lewis Baker, PhD

Director of Data Science

Alex Vaughan, PhD

Chief Science Officer

Kelly Trindel, PhD

Head of Policy & IO Science

Lori Foster, PhD

Head of Behavioral Science

Adrianne Pettiford, PhD

Head of Global Client Insights & Analytics

A broader community 

pymetrics is committed to contributing to scientific knowledge about ethical AI. We work with academics from a variety of disciplines including computer science, psychology, economics, and law, to provide new information about our technology that is transparent and useful for diverse audiences.