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.
Originality is Overrated (in Data Science and in Business)
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I recently met a brilliant data scientist who had built some amazing AI automation tools. But he kept saying things like “it’s not very original” and “I’m not building anything new, I’m just piecing together what’s there.” And I told him: “Your solutions don’t have to be original. They just have to solve the problem.” This is something I see all the time with technical people. They think they need to invent something revolutionary to be valuable. Here’s the thing… Your stakeholders don’t care if your solution is original. They care if it works. They don’t need you to reinvent the wheel. They just need you to use the wheels that exist to get them where they want to go. Some of the most successful businesses in the world are just better implementations of existing ideas. Uber didn’t invent taxis. They just repackaged ideas in a way that people found to be of value. Stop apologising for building practical solutions with existing tools. Start focusing on the value you create. 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 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...