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.
3 Books Every Data Scientist Should Read This Christmas (None of Them Are About Python)
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After spending most of the year in front of a screen, at Christmas time there’s nothing I enjoy more than finally switching off my computer and relaxing with a good book. With only 10 days left until Christmas, here are my top picks for this year’s holiday break: Stakeholder Whispering by Bill ShanderData scientists are constantly told of the importance of understanding their stakeholders’ needs. Unfortunately, this advice is rarely accompanied by instructions on just how to do this. In Stakeholder Whispering, Bill Shander fixes this gap. Stakeholder Whispering is a no-nonsense guide to uncovering what your stakeholders really want (not just what they ask for), interspersed with stories from Shander’s 30+ year career. Shander is an excellent storyteller, so the 222 pages seem to fly. Not convinced yet? Check out my interview with Shander for Value Driven Data Science. Hidden Potential by Adam GrantOne thing I love about data science is that, as a new profession, there’s more room for talented individuals to break through than in many more established fields. Success in data science rewards the right character traits, not just credentials and connections. In Hidden Potential, social scientist Adam Grant explores the science of achieving great things - both in your own life and in supporting others to achieve - and discovers what those character traits might be. It’s an eye-opening read that may change what you believe to be possible for you in 2026. Cain’s Jawbone by Torquemada (Edward Powys Mathers) Written in 1934 by the inventor of the cryptic crossword, Cain’s Jawbone is a murder mystery with a twist: the 100 pages are printed out of order. Your job is to solve the six murders by arranging the pages in the correct (unique) sequence. Back before the internet, supposedly only three readers ever solved it - it’s marketed as the “most fiendishly difficult literary puzzle ever written”. And even with Google’s help, the puzzle is still challenging. It took me 2 months to complete. But given data scientists’ affinity for puzzles, I can’t imagine a better way to spend your Christmas break. What books do you recommend for data scientists in need of a break? Hit reply and let me know. Talk again soon, Dr Genevieve Hayes p.s. I'm opening spots in my Strategic Expert Mentorship program starting in February 2026. This isn't a technical skills course. It's 1-on-1 mentorship for data professionals who want to make the move from technical executor to strategic expert. Between now and Christmas, I'm making time to talk with people who want to know more. Interested? 👉 Book Your Call Now |
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.
Data science bootcamps teach Python. They don’t teach you how to turn chaos into answerable questions. To this day, whenever I’m faced with a problem, the first thing I do is come up with a series of research questions - then I try to answer them. It’s standard practice in academic research, but I’ve rarely seen it done elsewhere. That experimental approach keeps me focused on what actually moves the needle. And it’s the kind of strategic thinking that gets you noticed by senior stakeholders....
My first month in industry as a data scientist, I drafted a beautifully structured email for my boss. What he actually sent was 1/10th the length. I’ve never felt more overeducated and underprepared. Fresh from my PhD, my boss asked me to draft an email for him. I spent 4 hours crafting what I thought was the perfect message: grammatically perfect, clearly justified, with every logical step meticulously explained - exactly how I’d been trained to write at university. When he CC’d me on what...
Imagine going to buy a house and the real estate agent just hands you a floorplan - without any photos or context. You’d see the number of bedrooms and bathrooms; the size of the house. All the important features. But would you buy it? Probably not. Because floorplans show features. People buy benefits. My parents’ neighbour recently moved house after 30+ years. For her new home, she chose a single-story house. The feature? No stairs. The benefit? Continued independence as she grows old - her...