About this episode

Ben Zweig discusses the evolution of data roles and the challenges in hiring within the data and AI fields.

The data field has changed shape faster than almost any other. The role that used to be a statistician became a data scientist, became an ML engineer, and is now morphing into AI engineer. Consulting firms are hiring fewer entry-level analysts and more vibe-coders who can ship AI systems to production. For data and AI professionals, this raises immediate questions. Which parts of the work are most exposed to automation, and which are not? Where should you invest your time? And which backgrounds are now producing the strongest hires, whether you are building a team or trying to join one? Ben Zweig is the CEO and Co-Founder of Revelio Labs , where he leads the development of a universal HR database built on over a billion public employment profiles and more than 5 billion job postings. He holds a PhD in Economics from the CUNY Graduate Center and teaches Data Science and The Future of Work at NYU Stern. Before founding Revelio Labs, he managed Workforce Analytics projects in the IBM Chief Analytics Office and worked as a data scientist at an emerging-markets hedge fund. He is the author of Job Architecture: Building a Workforce Intelligence Taxonomy . In the episode, Richie and Ben…

People in this episode

Host: Richie

Guest: Ben Zweig

Topics covered

• workforce analytics
• data science
• AI engineering
• hiring practices
• job market
• automation in jobs

Keywords

• data-driven workforce
• automation
• AI systems
• job postings
• data careers
• NLP
• LLMs

Mentioned in this episode

Organizations: Revelio Labs, IBM, NYU Stern

Books & works: Job Architecture: Building a Workforce Intelligence Taxonomy

Places: CUNY Graduate Center

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