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A Labor Market and Tech Hiring Deep Dive with Rhea Moss of iCIMS

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Manage episode 390619835 series 2796892
コンテンツは William Tincup によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、William Tincup またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal

Can companies find the talent they need in the current labor market? William Tincup and Rhea Moss, an expert from iCIMS, tackle this question together. As the leader of iCIMS' insights program, Moss brings her extensive research experience to shed light on the aggregate activity of iCIMS' customer base, consisting of 6,000 companies. The labor market is pretty complex, which means we're going to need some efficient recruitment strategies to stay ahead of the game.
Throughout the conversation, Moss provides valuable data-driven insights into job applications, hiring trends, and time-to-fill statistics. The duo delves into the paradoxical dynamics of the labor market, where a surge in the number of applicants for technical positions contrasts with a slowdown in technical hiring. They investigate the reasons behind this phenomenon, such as companies' hesitancy to invest in new projects and talent amidst economic uncertainties.
Another crucial aspect of their discussion involves the potential impact of generative AI on the supply of technical talent. Moss emphasizes the importance of human involvement in critical decision-making processes, highlighting the unique insights and understanding that human professionals bring to the table. While AI can enhance efficiency, the expertise and judgment of recruiters remain indispensable.
There's a myriad of challenges and opportunities in this ever-evolving tech hiring landscape, so let's try to make sense of it together!
Listen & Subscribe on your favorite platform
Apple | Spotify | Google | Amazon
Visit us at RecruitingDaily for all of your recruiting, sourcing, and HR content.
Follow on Twitter @RecruitingDaily
Attend one of our #HRTX Events

  continue reading

617 つのエピソード

Artwork
iconシェア
 
Manage episode 390619835 series 2796892
コンテンツは William Tincup によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、William Tincup またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal

Can companies find the talent they need in the current labor market? William Tincup and Rhea Moss, an expert from iCIMS, tackle this question together. As the leader of iCIMS' insights program, Moss brings her extensive research experience to shed light on the aggregate activity of iCIMS' customer base, consisting of 6,000 companies. The labor market is pretty complex, which means we're going to need some efficient recruitment strategies to stay ahead of the game.
Throughout the conversation, Moss provides valuable data-driven insights into job applications, hiring trends, and time-to-fill statistics. The duo delves into the paradoxical dynamics of the labor market, where a surge in the number of applicants for technical positions contrasts with a slowdown in technical hiring. They investigate the reasons behind this phenomenon, such as companies' hesitancy to invest in new projects and talent amidst economic uncertainties.
Another crucial aspect of their discussion involves the potential impact of generative AI on the supply of technical talent. Moss emphasizes the importance of human involvement in critical decision-making processes, highlighting the unique insights and understanding that human professionals bring to the table. While AI can enhance efficiency, the expertise and judgment of recruiters remain indispensable.
There's a myriad of challenges and opportunities in this ever-evolving tech hiring landscape, so let's try to make sense of it together!
Listen & Subscribe on your favorite platform
Apple | Spotify | Google | Amazon
Visit us at RecruitingDaily for all of your recruiting, sourcing, and HR content.
Follow on Twitter @RecruitingDaily
Attend one of our #HRTX Events

  continue reading

617 つのエピソード

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