Data analytics reveals correlations between employee demographics and employee success using the historical hiring records and current employee files. This product helps prioritize interviews and improve hiring practices.
Through machine learning and entity extraction techniques profiles are developed for the ideal job applications, and applications are automatically scored to prioritize interviews. Some example profiles in retail might include:
Entry level: Ages 17-24, Previous experience includes working in restaurants, typically come from moderate income neighborhoods. Live no more than 15-20 minutes from the workplace.
Mid-manager: 3-6 years retail experience, own a single family home, live no more than 40 minutes from the workplace.