As we approach episode #900, the original SuperDataScience Podcast host Kirill Eremenko returns to reflect on what leads to the highest-paying opportunities in AI. This is a special one; enjoy!

Many of you will already know Kirill:

Founder and CEO of SuperDataScience.com, the eponymous e-learning platform.
Founded the SuperDataScience Podcast nine years ago and hosted the show until he passed me the reins five years ago.
With over 3 million students, he’s the most popular data science and A.I. instructor on Udemy.
He holds a Master’s from The University of Queensland in Australia and a Bachelor’s in Applied Physics and Mathematics from the Moscow Institute of Physics and Technology.

Today’s episode is ideal for anyone looking to advance their data science or A.I. career — or looking to break into a career in this field for the first time.

In today’s episode, Kirill details:

Why employers are still testing A.I. engineers on basic machine learning fundamentals — even for LLM-focused roles.
The surprising reason why staying in data science (as opposed to developing an A.I. specialization) could be the right career move for you.
How one developer discovered the hidden age bias in tech recruiting — and the simple hack to beat it.
The two critical skill areas that separate amateur A.I. engineers from the pros commanding huge salaries.
Why the "back to office" movement could give you a competitive advantage in landing a top A.I. role.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.