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.
My 3 Major Career Pivots in Data Science
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I’ve made three major career pivots in data science. None of them involved climbing a ladder. I thought academia was going to be my forever job. I imagined being in a university until the day I retired - possibly until I died, because academics last forever. Then I got to the end of my PhD and realised: I don’t actually want to spend the rest of my life in school. So, I made my first career pivot - from academic to insurance pricing manager. A few years later, I heard about this exciting new thing called data science. Instead of leaving my job to chase it, I convinced my boss to expand my team’s remit. We became the actuarial and data science team. That was my second pivot. Then COVID hit. I had time to rethink everything. I realised if I kept doing what I was doing, it was going to become Groundhog Day. So, I made my third pivot - leaving corporate to start my own data consultancy. Each pivot taught me something new about creating value as a data professional. And the biggest lesson of all? You’re not stuck following the one career path. You can pivot, experiment, and build on what you’ve already learned. I unpacked all of this (and more) in my recent conversation on the unDubbed podcast with hosts Sarah Burnett and Fi Crocker. This approach transformed my career. It might transform yours, too. 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.
ChatGPT just got destroyed at chess by a 46-year-old Atari 2600 console. And as someone who owned that exact console as a kid, I find this absolutely hilarious. My Atari 2600 was a hand-me-down from my cousin. And even as a kid in the early 1990s, I could see it wasn’t great. By today’s standards, though, it seems far, far worse. The Atari 2600 has about 1/250,000 the processing power of an iPhone 15 Pro. By comparison, ChatGPT runs on data centres worth hundreds of millions of dollars. Yet,...
Growing up, my parents had arts degrees and couldn’t understand a word I said about maths or science. Every dinner conversation went something like this: My parents: “What did you learn at school today?” Me: “In maths, we learned about differential equations.” My parents: 😕 “So… is that a good thing or a bad thing?” At the time, I thought this was incredibly frustrating. However, I now realise it was the best training I could have gotten for my data science career. Because when you spend...
When it comes to building a career, every data scientist is running their own business - it’s just that most of those businesses are solo operations with one client: their employer. Think about it. To succeed in data science, you need to: Market your skills internally; Find opportunities for new projects; Manage stakeholder relationships; Deliver value and try to ensure repeat “customers” (in the form of more interesting work). The are all skills required to succeed in solo consulting. The...