The tech job market, particularly for entry-level roles in computer science and engineering, is undergoing a significant "reset" characterized by a collapse in new graduate hiring and a widening talent gap. While AI is a contributing factor, the primary drivers are a tightening funding environment, overhiring during the pandemic, and an increased employer demand for demonstrable skills and experience over raw potential.
This has created an "experience paradox" where new grads struggle to gain the necessary experience to secure jobs. However, a critical counter-trend highlights a surging demand for roles requiring strong mathematical foundations, as these skills are essential for powering the next generation of AI products and infrastructure, offering a "future-proof" pathway for those who adapt.
About this Podcast
This is our new experimental AI-narrated pod, featuring content written by humans, aimed at making abstract mathematics more accessible and less intimidating for technical audiences without a formal background in higher mathematics. Our goal is to spark your curiosity and encourage you to explore advanced branches of mathematics.
Most of the content is developed in-house by our team, but we also draw on high-quality open-source materials, including articles and blog posts, which are properly referenced in each episode.
Enjoy listening!
QF Academy team
Share this post