Why Hiring and Retaining Top AI Talent Has Become Harder Than Ever
Show notes
With Misha Trubskyy — Head of Claims Data Science, Mercury Insurance
Why is hiring exceptional AI and Data talent still so difficult even in a market full of candidates?
In this episode, Ben Parker speaks with Misha Trubskyy about what organisations are getting wrong when hiring, assessing and retaining AI and Data professionals.
Drawing on his experience leading Data Science in insurance, Misha explores the disconnect between companies struggling to find the right skills and candidates who feel hiring processes have become too selective.
The conversation examines what leaders should really look for beyond technical ability, why critical thinking and authenticity matter, and what organisations need to do differently to keep their strongest people once they've hired them.
You’ll hear practical insights on:
- Why AI and Data talent remains difficult to hire
- The disconnect between employers and candidates
- What actually separates exceptional candidates
- Why technical skills alone aren't enough
- How to assess critical thinking and real-world capability
- The case for investing in junior talent
- What keeps top AI and Data professionals from leaving
- How the talent market could evolve over the next few years
Chapters
00:00 Introduction
02:24 Misha's career and leadership journey
07:37 Lessons in leading Data Science teams
29:52 Why hiring AI & Data talent is so difficult
37:02 What to look for beyond technical skills
44:21 What's happening in the talent market
48:55 Why organisations should invest in junior talent
01:04:33 How to retain top performers
01:10:03 The future of AI & Data hiring
Thank you for listening!