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.
Four Technical Degrees Taught Me Nothing About This
|
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. Perfectly match the assignment specs. Simple, once you know the rules. Many data scientists I've met have similar stories. Here's the thing... Despite landing me my first jobs, my early academic success ultimately set me up for career failure. I expected that continuing to follow instructions and deliver high-quality work would lead to rapid promotion - instead it just kept me stuck. The breakthrough for me came by pure chance. I was chatting with a senior stakeholder about a problem she was facing. I told her how I'd solve it - nothing very complex. But to my surprise, she looked at me and said "OK. Go do it.". Years of hard work executing "perfectly" on others' tasks hadn't gotten me far. But that one simple solution, that I proposed myself, got me the promotion I so desperately desired. That's when I realised the rules of the game had changed. Perfect execution was no longer the key - identifying high value problems and solving them was what really mattered. School assignments were only ever meant for skill acquisition. Assignment creation is what counts in the business world. So if you're looking for career growth here's my question for you: Are you waiting for better assignments to drop in your lap, or are you actively looking for problems worth solving? Your answer may determine where your career goes from here. Talk again soon, Dr Genevieve Hayes. p.s. I'm launching something special next week to help data scientists create these breakthrough moments deliberately rather than leaving them to chance. 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 13, 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.
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...