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.
The Irony of Scalability
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Data science is obsessed with scalability. Can your model handle bigger data received at a higher velocity than ever before? So, it's ironic that some of the best things you can do for your data science career don't actually scale. Genuinely understanding the problems of a single stakeholder - doesn't scale. Building a reputation as an expert in your domain - doesn't scale. Delivering recommendations that actually get acted on - doesn't scale. AI has made it easier than ever to produce technical work at scale. This means the things that can't be scaled are worth more than ever before. 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.
Shortly after starting work in a new role, I was assigned responsibility for a data report that my predecessor, “Charlie”, had previously maintained. The report was scheduled to run on the first day of each month and had been used for years, seemingly without a hitch. However, on examining the code behind the report to figure out how it worked, I was shocked to discover a small calculation error that meant every report run to that point had actually been wrong. Not obviously wrong. The...
Correlation does not equal causation. Every data scientist has had that drummed into them. In fact, when I taught data science, I used to be the one doing the drumming. However, as every data nerd’s favourite comic, “xkcd”, once pointed out: correlation “does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there’”. This is the part most data scientists miss. Without correlation, there can be no causation and often, it’s because researchers noted the existence...
I once worked in an organisation where every member of the data science team was assigned an $8,000 laptop. It sounds way cooler than it was. We’re not talking about the Rolls-Royce of MacBooks here. Rather, it was a massive brick of a device that ran Ubuntu Linux and was so heavy it rarely left my desk. My team had convinced our employer to buy them because fitting the machine learning models we needed required powerful GPUs - and with security concerns limiting our cloud access, this was...