Removing bias

Game design to reduce bias embedded in the structures of traditional assessments - for example, women and minorities fare worse than men on standardized tests and our game design corrects for this.

Blind auditions to mitigate conscious and unconscious biases - candidates move through our platform completely anonymously, and the prediction algorithm does not use demographic information to assess career fit.

Statistical tools to remove residual bias - our platform goes a step beyond the usual, complementing game design and the blinding process by removing residual bias.


The pymetrics games were developed by the global neuroscience community over decades of research.

The games measure key cognitive traits, providing a snapshot of a person's unique characteristics.

Your cognitive profile is built based on your game performance.

Data science

Sophisticated, bias-free data science algorithms are applied to your personalized cognitive profile.

We match your profile to career profiles we've built based on the game performance of successful professionals.

Get hired! We'll find you job openings in careers where your inherent traits lead to success.

Our science is legit

and we have the degrees to back it up

Dr. Frida Polli
Postdoctoral fellow in Brain and Cognitive Sciences, MIT
Predoctoral fellow in Psychiatric Neuroimaging, MGH / Harvard
PhD in Neuropsychology, Suffolk University
MBA, Harvard Business School; BA, English, Dartmouth
As a pre- and postdoctoral fellow at Harvard and MIT, Dr. Polli studied cognitive and emotional processing in healthy controls and psychiatric conditions. She has more than 30 publications, conferences presentations and plenary talks. She has 11 awards in neuroscience including several National Research Service Awards from the NIH, as well as a NARSAD Young Investigator Award. She won the MIT Life Sciences Track Entrepreneurship Competition in 2010.
Dr. Julie Yoo
Postdoctoral fellow in Brain and Cognitive Sciences, MIT
PhD, Health Sciences and Technology, Harvard / MIT
BS and MS, Electrical and Computer Engineering, University of Waterloo
As a postdoctoral fellow at MIT, Dr. Yoo earned grants from the Department of Defense. Her research included using machine learning to predict optimal learning time based on real-time neuroimaging data, and building automatic speech recognition machines. Her predictive algorithms have been featured in academic journals as well as the Wall Street Journal.
Dr. Matt Malter Cohen
PhD in Neuroscience, Weill Cornell Medical College
MA in Psychology, Columbia; BS in Psychology from Carnegie Mellon.
Dr. Malter Cohen completed his dissertation work at Cornell in Dr. BJ Casey’s lab. As an expert in research methods and design, he has integrated cross-species methodologies that span genetics, molecular biology, psychophysiology, various neuroimaging technologies, and psychology. Matthew has been an invited speaker at MIT and Carnegie Mellon, and numerous publications in PNAS, Neuroscience, Neuron and Biological Psychiatry.