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.
Data Science Lessons from a Reformed Social Media Hacker
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What can ethical data scientists learn from a social media hacker? More than you might think. Tim O'Hearn is a software engineer who spent years circumventing anti-botting measures and gaining millions of followers for clients - experiences he's chronicled in the recently published Framed: A Villain’s Perspective on Social Media. Not exactly the typical guest you'd expect on a data science podcast. Here's the thing... Understanding how systems can be exploited makes you better at building robust, reliable models. Tim gained millions of followers for clients by circumventing platform safeguards. His approach wasn't about "beating the algorithm" - it was about understanding bot detection systems so well that he could operate just under the radar. In the latest episode of Value Driven Data Science, Tim joins me to share insights from his experience manipulating social media platforms, revealing what ethical data scientists can learn from understanding the dark side of algorithmic systems. This conversation reveals:
This isn't about encouraging unethical behaviour. It's about understanding vulnerabilities so you can build better, more resilient systems. 🎧 Listen now on Apple Podcasts or Spotify, or click the link below: Talk again soon, Dr Genevieve Hayes. p.s. I'm launching something special next week to help data scientists move from waiting for assignments to creating their own strategic opportunities. It's a 4-week program where I'll work with you 1-on-1 to develop a ready-to-pitch project proposal that showcases your strategic thinking to management. Only 3-5 spots are available, with sessions starting in July-August 2025. Reply with the word "WAITLIST" to join the waiting list and get all the details this Friday - 3 days before Monday's official launch! First published: July 16, 2025 |
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.
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