Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
Knowledge is No Longer Enough
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“Cheating with artificial intelligence is now rampant at universities.” “University is no longer a test of your intellect. It’s a test of how well you can instruct Chat GPT.” “AI Is giving students top grades for zero intellectual work.” These are quotes from a recent article in The Australian Weekend Magazine, which argues that students are now turning to AI en masse to automate learning, and graduating with perfect grades but limited knowledge. The phenomenon has been observed across multiple degrees, so presumably data science students aren’t exempt. Here’s what this means for working data scientists: If AI can now ace a university degree, your competition for the next “big opportunity” isn’t just the data scientist at the desk next to you - it’s also the AI doing the degree. You can’t compete on knowledge alone anymore. Knowledge is increasingly commodified and automatable. You need to compete on expertise - the combination of knowledge and experience that’s much harder to automate. The technical foundations still matter - you can’t fake your way through real work forever. But they’re table stakes now, not differentiators. What separates you is what you’ve learned by actually doing the work. Talk again soon, Dr Genevieve Hayes |
Data Science Impact Algorithm
Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
When I started my career, data science didn’t exist as a field. I trained as an actuary and statistician and those were the tools I relied on in my earliest roles. Then, around 10 years ago, I started hearing about the wonders of machine learning and became worried that my traditional training was no longer enough. So, despite already having a PhD in Statistics, I went back and completed a Masters in Machine Learning. Then came the AI wave – ChatGPT, large language models, generative AI – and...
The most valuable lessons I’ve learned in my data science career weren’t learned in a classroom. They came from conversations with people who’d already figured things out the hard way. My podcast has been a more valuable learning tool for me than all of my university degrees combined. Over 100 episodes, I’ve had the chance to speak one-on-one with some of the sharpest minds in the industry - CEOs, best-selling authors and leading researchers - on everything from cutting-edge AI to what it...
In 2015, I fell in love with a job I would never have. I’d just attended a conference where people were talking about machine learning and data science as the way of the future. I returned to the office eager to learn more and started down the data science rabbit hole - where I stumbled across an article about the recently established NYC Mayor’s Office for Data Analytics. They were using data science to locate illegal cooking oil dumping in the city’s sewers. To coordinate emergency services...