Our team have published a book about the techniques they use.
Case Study 1:
An American multinational technology corporation was receiving thousands of applications a month and wanted an algorithm to identify which candidates to engage for specialized technology positions.
CASE STUDY 2:
A global recruitment agency must trawl through a large database of candidates against thousands of open positions. Their search turns up excessive “false positives”, misses high quality candidates, wasting revenue opportunities and time.
Case Study 3:
An HR-tech company with 150+ corporate clients wanted a way to identify predictive variables to develop customised candidate marketing & recruitment campaigns that improve candidate engagement.
Case STudy 4:
A Hyper-Growth Recruitment Agency - GQR - wanted to automate many aspects of the search process, use matching to drive engagement and systematically label resumes across 350,000 records.
Our Chief Data Scientist Jon Krohn regularly appears on podcasts, speaks at conferences, lectures online and has published Deep Learning Illustrated.
Some of his work can be found here:
Podcast on making sense of the growing global data
Blog post on “Bias free hiring”
Meet ups about Deep learning
Conferences - Talking about what he knows best - Deep learning