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A graphic of the AdeptID logo and the Multiverse logo in green circles

Multiverse team up with AdeptID to utilize machine learning for equitable talent matching

Today we’re delighted to announce a new partnership with AdeptID, the leading provider of talent matching software for the workforce without college degrees. Together we’ll use their machine learning models to scale up and optimize our processes for matching apprentices with employers.

At Multiverse, we’re obsessed by two things: equitable hiring and data-driven decision making. They are essential to delivering our mission of creating a diverse group of future leaders and this new partnership will help us make progress on both of them.

We fundamentally believe there is no link between academic achievement and job performance. In the US, degree requirements in job ads screen out 67% of black Americans and 79% of Hispanic Americans. Talent is everywhere but opportunity often is not.

Our belief has always been that the things that actually correlate to job performance are around character, grit, conscientiousness and willingness to learn. Too often grades are a function of how good someone’s school was rather than their actual potential.

We built our model of matching apprentices to employers to include that more inclusive definition of potential. Our work with 

 will help us to put new layers of data analysis behind the model.

So far we’ve placed thousands of apprentices in their first roles. They are hugely talented, and come from a 

. Getting to tens of thousands, and eventually hundreds of thousands, will require a larger scale. AdeptID’s technology helps us set up a “feedback loop” so that we are continuously learning from these placement outcomes to make better recommendations.

The team at AdeptID brings a rigorous and responsible approach to machine learning to help identify talent in those without college degrees. Most importantly, they align totally to our mission. Learn more about their approach here.

We’re excited for what we get to do together.

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