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.
11 Bosses in 3 1/2 Years Taught Me This Valuable Lesson
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Quick reminder: Doors close for the Data Science Impact Sprint at the end of the week. If you're interested in boosting your strategic influence and positioning yourself for career advancement, consider joining. Scroll down to learn more...
In 3 1/2 years, I had 11 managers across 2 data science roles. Let that sink in for a bit... That's an average of around 4 months per boss (and I'm not counting the short-term acting managers when people went on leave). This has got to be some sort of record. Restructures, secondments and even a retirement - my world was a revolving door of leadership. No sooner had a manager settled into a new role than one of us would move on to the next. Forget about developing my career - they were too busy figuring out their own. Here's the thing... That's OK. Because here's what I learned: you can't build a career waiting for other people to create opportunities for you. Managers come and go. Restructures happen. But your career? That's yours to manage. A few bosses in, I got tired of waiting. I started identifying problems worth solving and proposing projects of my own. I noticed IT was struggling to understand the different AI APIs across cloud platforms. So I did a comparative study - something no one had asked for, but everyone needed. This was mid-2020, during the COVID lockdowns. I had zero budget and inadequate resources. So, I set up my own trial accounts and created test data - I filmed a Rice Bubbles box to test video object recognition, tested OCR using photographs of t-shirts on my washing line and used audio from Presidential debates to test transcription. The report went "viral". I became "the AI cloud expert" and got invited to all meetings related to AI. One scrappy project I initiated myself - because I couldn't rely on my 11 managers to do it for me. While my managers were figuring out their careers, I figured out how to advance my own. If you're tired of waiting for someone else to manage your data science career, here's your chance to start managing it yourself. The Data Science Impact Sprint closes at the end of this week - my 4-week 1-on-1 coaching program that teaches you to create high-value data science opportunities that will boost your strategic influence and help position you for career advancement. Reply with the word 'SPRINT' for details. Only 3-5 spots are available for this pilot program. Doors close at 9am on Saturday 2nd August Melbourne, Australia Time (7pm Friday 1st August US EDT) or when all the places fill. 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.
Like most data scientists, I started my career in traditional 9-to-5 roles. With bills to pay and limited experience, a regular job felt "safe". Then COVID hit. Nothing felt "safe" anymore, and my dreams of working for myself no longer seemed so insane. I finally made the leap - and never looked back. Many data scientists share similar dreams of breaking free from traditional employment, but don't know where to begin. Yet, here's what I've learned along the way: there's no single path to data...
A data scientist I know once told me of a manager who would end every team meeting with the same advice: “keep kicking goals.” What does that even mean? Which goals? With what resources? How do you even measure what a goal is? Unless you’re actually talking to a football team, “keep kicking goals” is meaningless. Yet this is what some data scientists face. Well-meaning managers who say “go do data science” without giving direction on what that actually requires. And then they wonder why...
Want to know the book that's had the greatest influence on my thinking as a data scientist? I bet you'll never guess. It's Jurassic Park (the book, that is - definitely NOT the movie). As a teenager, I read everything I could find by Michael Crichton and his message of focusing on solving the problem while ignoring all irrelevant distractions still influences the way I work. Whenever I feel overwhelmed in my work, that's what I remind myself. I've been doing it for decades and will do it for...