The number of migrant workers working as domestic workers are increasing in many major cities around the world, mainly because of aging population and the rise in two-income families. This thesis introduces a job matching system for employers and foreign domestic workers to find their right matches. There are three main ideas being discussed in the thesis : Firstly, the application of machine learning techniques such as spam detection and topic modelling in the system. Secondly, the applications of design-thinking, growth-hacking and “Don’t make me Think” approaches in product development. Thirdly, the business processes involved in the system. The premise of the whole study intersects machine learning, product design, and entrepreneurship. The job-matching platform was launched...[ Read more ]

The number of migrant workers working as domestic workers are increasing in many major cities around the world, mainly because of aging population and the rise in two-income families. This thesis introduces a job matching system for employers and foreign domestic workers to find their right matches. There are three main ideas being discussed in the thesis : Firstly, the application of machine learning techniques such as spam detection and topic modelling in the system. Secondly, the applications of design-thinking, growth-hacking and “Don’t make me Think” approaches in product development. Thirdly, the business processes involved in the system. The premise of the whole study intersects machine learning, product design, and entrepreneurship. The job-matching platform was launched in September 2017 and generated 100,000 users in just three months.