VDAB’s mission is to help every job seeker find their dream job.
We helped improve the job seeker experience at the Dutch public employment service, VDAB. By offering personalized recommendations, we helped increase the number of job applications through their various digital channels.
ObjectiveOur client’s mission is to help every job seeker find their dream job. Our solution is helping them achieve that.
How?A job recommender has to predict how likely a job seeker will be interested in a vacancy, based on everything it knows about that job seeker and that vacancy. We built a Deep Learning model that accurately predicts job interest, by learning from millions of historical interest signals.
Classical, rule-based systems achieve this goal by manually defining matching criteria. For example: “To work as an engineer, you need an engineering degree”. This is a fragile system, which often doesn’t return the most relevant suggestions. What if, instead of defining the rules manually, we could learn those rules from the millions of historical examples of job seekers who applied for certain jobs? This is exactly what we did. We built a Deep Learning model that takes as input profiles of job seekers, job vacancies, and historical interest signals between them. The model learns to predict these interest signals. For example: “I often see Psychology majors applying for HR-related jobs, so I will remember this relation because this helps me correctly predicting interest signals”.