Find the right match.
Skip the CV pile.
An Azure-based recommendation system matches consultants to opportunities, giving managers more time for sourcing, negotiation and onboarding.
Algorhythm Group, our parent company
The challenge
Our parent company, Algorhythm Group, assigns its consultants to new opportunities at clients. Business unit managers screen job offers and CVs to find the right match for the consultants in their unit.
As Algorhythm Group and the number of available offers grow, manually screening and matching hundreds of CVs to new job offers becomes more and more challenging.
The business unit managers would rather spend their time on more meaningful work than going through these documents by hand.
The solution
Our team set up a data architecture on Azure to collect, clean and process job offer data and consultants' CVs.
Using natural language processing and AI, we trained a recommendation model that matches job offers to consultants based on their CVs and business unit (domain of expertise). The model was trained and served to end users on Azure Machine Learning. Continuous monitoring tracks its performance, and the model is retrained in production when needed.
The result
Business unit managers instantly receive job offers matched to candidate consultants in their unit.
They no longer have to go through endless documents to screen and match consultants and offers by hand. That frees up time for more important work, like sourcing, negotiation and onboarding.