February 3, 2020
Case Study Hr Automated

HR Automated

The Problem A fortune 500 Hedge Fund was looking to quantify beneficial hiring characteristics and to develop predictive hiring indicators to filter candidate applications. They had 10 years of unstructured free-text, both through resumes, third-party data, and interview notes. This contained large amounts of unstructured (free text, scans, emails) data. They were looking to standardize this data for improved analysis and to reveal non-standard correlative […]
December 27, 2019

Removing Bias from Hiring with Natural Language Processing

THE CHALLENGE Resumes are inconsistent. Even the best OCR parsing leaves you with lots of messy and unstructured data. Then, as a candidate moves through the application process, humans get involved. Add to the data set free form text reviews of the applicant and both linguistic and personal biases. In addition, each data source is siloed providing limited analytical opportunity. SERVICES Machine Learning NLP People […]
September 20, 2016
Machine Learning Hiring Platform

Machine Learning Hiring Platform

The Problem Uiba offers Machine Learning for Organizational Management to medium and large-sized organizations. This platform enables their clients to hire, allocate, and develop their workforce in a manner designed to maximize productivity, minimize cost, and achieve optimal efficiency. Blue Orange developed and designed the first version of its platform. Sector Tech Vertical Talent Analytics Model SVM/Random Forest Case Study Uiba required a Machine Learning […]