In Washington D.C., metro ridership is only 30 percent of the 2019 ridership. The hustle and bustle of the city has not returned as employers are uncertain on when and how to reopen offices due to the Delta variant and at present Omicron. A Capital Covid survey conducted by the Greater Washington Partnership revealed that less than half of employees were expected to be back in the office on an average workday this fall.
Despite the increasing job advertisements, what raised more concerns, however, is that the unemployment rate remains high. The long-term unemployment rate keeps rising at the fastest rate in a decade and the unemployment claims are still double the size compared to the time before the pandemic.
The Federal Councillor’s solemnly echoing speech at the inauguration of the new office complex of a well-known technology company near Zurich Main Station booms from all the loudspeakers. Although baggage handler Mario is only half paying attention, the omnipresent buzzwords “digitization” and “innovation” cannot be overheard.
This is the second in a series of posts on machine learning in HR tech. If you haven’t already, we recommend you read the first post here.
In our last post, we explained why it takes more than data science and machine learning (ML) to build a knowledge graph for a job matching system. In a nutshell, to build a knowledge representation of sufficient quality, you need people who understand the knowledge you want to represent.
Despite improvement, there will still be a significant gap between supply and demand of healthcare staff by 2029 in Switzerland, according to the national 2021 report on future healthcare staff needs, published by the Swiss Health Observatory in September.
Many job matching and recommendation engines currently on the market are based on machine learning (ML) and promoted as revolutionizing HR tech. However, despite all the work put into improving models, approaches and data over the past decade, the results are still far from what users, developers and data scientists hope for.
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