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.
AI Boom, AI Doom, and Everything in Between
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I spend a lot of time talking to data professionals about AI, and one thing I’ve noticed is that attitudes typically fall into one of two extremes: AI boom or AI doom. At one extreme are those who are excited about the new opportunities AI will create - the chance to do more interesting work or finally launch the business they’ve always dreamed about. These people are always eager to share what they’ve used AI to create, and the results invariably amaze. But at the other end are those who lie awake at night, wondering if their job will still exist in 12 months’ time, saving every dollar they can for when the job apocalypse finally arrives. I even had one data scientist recently tell me they would be happy if the entire AI industry crashed and burned. Yet, regardless of where they fall on that spectrum, few of the data professionals I’ve spoken to have a clear sense of what to do next. What skills should they be building today to be ready for tomorrow? Nicholas Kelly, author of Delivering Data Analytics and The AI-Driven Data Team, had his own version of that moment of uncertainty. Two years ago, a client told him bluntly that ChatGPT could do 50% of what he did and they wouldn’t be needing his dashboard-building services anymore. Rather than waiting to see what happened next, Nick made a choice: get ahead of it and decide what his career becomes, instead of waiting to find out what happens to it. In the latest episode of Value Driven Data Science, Nick joins me to share what that evolution looked like in practice, what data professionals at any stage of their career can learn from his experience and why their existing expertise puts them in a stronger position than they might think. You’ll discover:
The AI era presents a choice: wait to see what happens to your role, or get ahead of it and decide what it becomes. Which are you going to choose? Listen now on Apple Podcasts or Spotify, or click the link below: Episode 115: Evolving Your Data Career for the AI Era 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’m looking for guests for my podcast, the first place I turn is invariably my bookcase. The authors of data science books have already demonstrated their authority in the field to the point of developing their own original IP. That makes them ideally suited to a podcast about data science expertise. And it’s no coincidence that many of those authors started off by writing blogs. It turns out conference organisers do something similar. When Cynthia Dunlop, who helps organise two major...
A couple of years back, I watched a TV series called The Fear Index. The series focused on a hedge-fund manager who had developed an AI system to optimise fund profits. Of course, as you would expect for a TV show - 🚨Spoiler Alert🚨 - everything falls apart when the AI starts taking highly illegal and frequently fatal actions in order to drive the market and achieve its goals. I enjoyed the show immensely, but at the time, felt it was far-fetched. However, recent reports of an OpenAI agent...
It’s no secret that many data scientists chose this profession in part because they enjoyed maths and wanted to avoid writing essays. When I was managing a data team, my team members would happily spend hours writing code. But ask them to write up what they’d done and suddenly everyone was too busy. Getting them to document their results in the form of a report was a lot like pulling teeth. And I understood why - to them, writing felt like a distraction from the “real” work. But over time, I...