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.
How to Trust Data You Know has Been Manipulated
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How do you extract trustworthy insights from data you know has been deliberately manipulated? It's a challenge most data scientists never face. We're used to cleaning messy data, but deliberately manipulated data? That's completely next level. Yet if you're working with social media data, manipulation is the reality you're dealing with. Tim O'Hearn, a reformed social media hacker who generated millions of followers through bot manipulation, recently shared with me the harsh reality: "During what I would describe as the golden age of Instagram botting, (the proportion of fake accounts) was probably as high as 40%." Let that sink in for a moment. If you're making business decisions based on social media data, nearly half of what you're analysing could be artificial bot activity. And if you're attributing value to social media accounts without filtering for bots, you're potentially wasting 10-20% of your marketing budget on fake audiences. The good news is there are ways to identify and filter out this manipulated data - techniques that can also apply to identifying suspicious records in any dataset. In the latest episode of Value Driven Data Science, Tim joins me again to reveal practical strategies for identifying and filtering out bot activity from social media datasets to extract trustworthy business insights. This Value Boost episode uncovers:
Essential listening for anyone working with social media data. 🎧 Listen now on Apple Podcasts or Spotify, or click the link below: Talk again soon, Dr Genevieve Hayes. p.s. Next month, I'm teaching 3-5 data scientists my complete process for creating your own high-value data science opportunities in the Data Science Impact Sprint - a 4-week, 1-on-1 coaching program that will boost your strategic influence and help position you for career advancement. Reply with "SPRINT" and I'll send you the details. Doors close at 9am on Saturday 2nd August Melbourne, Australia Time (7pm Friday 1st August US EDT) or when all the places fill. First published: July 23, 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.
Before we begin: Next month, I'm teaching 3-5 data scientists my complete process for creating your own high-value data science opportunities in the Data Science Impact Sprint - a 4-week, 1-on-1 coaching program that will boost your strategic influence and help position you for career advancement. Scroll down to learn more... They say you should start the job you want before you have it. Back in 2015, I wanted to be a data science manager. The problem? Data science was new. Data science...
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...
Years of delivering "perfectly" on complex data science assignments got me nowhere. One simple solution I proposed myself got me promoted... The last time I received a grade of less than an A was when I was 15 and forced to do P.E. Since then, I went on to complete 4 degrees - all with perfect GPAs. I'm not saying this to brag, but rather to make a point. I was the poster-child for academic success. What it all came down to was learning how to play the game. Put in the hours of hard work....