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.
It's Not AI that will Take Your Job
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Each week, it seems like there’s yet another announcement of technical workers losing their jobs to AI. In Australia, for example, tech giant Atlassian recently laid off 1,600 workers - 10% of their global workforce - “to steer more spending into AI”. Now, granted, not every AI-related job loss is necessarily as it first appears. Some experts point to AI-washing. That is, companies using AI as cover for restructuring decisions they would have made anyway. But regardless of the reason, the reality is that AI has fundamentally changed the nature of white-collar work. And for technical workers, including data professionals, it raises the uncomfortable question: if AI can do what you do, why would anyone need you? The solution, according to Tim Dietrich, isn’t to compete with AI. It’s to harness it as a force multiplier - expanding what you can deliver, taking on work you couldn’t have touched before, and making yourself not just relevant, but indispensable. As technical professionals experienced in working with cutting-edge software tools, we are better placed to do this than most. Tim is a software developer with over 25 years of experience. Until about nine months ago, he described himself as “the world’s most negative person on AI”. He was convinced it was overhyped and quietly hoping he could make it to retirement before it affected his work. He didn’t make it that far. But what he built instead is far more interesting. In the latest episode of Value Driven Data Science, Tim joins me to share how he built a virtual team of over 100 AI specialists that allows him to operate with the output and breadth of a small firm - while remaining a team of one. You’ll discover:
The question isn't whether AI will change your work. It's whether you'll be ahead of that change or behind it. Listen now on Apple Podcasts or Spotify, or click the link below: Episode 107: Building a Virtual Empire of AI Specialists 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.
Have you ever seen the TV show Nip/Tuck? It centres on the lives and clients of two Miami plastic surgeons. But what it’s really about is the quest for perfection. The main characters want perfection in their own lives, but all they are actually capable of creating is the illusion of it. And beneath the perfect facades, all the characters are actually pretty terrible. It’s now over 20 years old, but rewatching an episode the other day made me realise it serves as a perfect metaphor for AI. AI...
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In a recent blog post, CFO advisor and friend of the list Lauren Pearl discussed the impact of AI on the age-old software “build vs buy” decision. In short, Lauren argued that AI-driven vibe coding has made building software in-house far more appealing when the stakes are low, but when stakes are high, buying is still the way to go. To quote Lauren: “When you buy software, you don’t just buy the code. You buy a support team, expert-derived flows, tested features, platform trust, regular...