Case Study 1:
An American multinational technology corporation was receiving thousands of applications a month and wanted a way to identify which candidates to engage with quickly for specialized technology positions.
CASE STUDY 2:
A global recruitment agency mines a large database of candidates against thousands of open opportunities that they work each year. Their search identifies excessive “false positives”, misses high quality candidates, wasting revenue opportunity 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 wanted to cleanse it’s CRM by systematically labelling profiles across 350,000 records.
Our team have published a book about the techniques they use.
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
Podcast - Explaining AI in recruitment
Blog post on “Bias free hiring”
Meet ups about Deep learning
Conferences - Talking about what he knows best - Deep learning