The Accidental Data Scientist

Welcome to The Accidental Data Scientists—a not-so-subtle nod to the legendary George Box and his autobiography, which you should absolutely read. Box famously said he didn’t choose to become a statistician; necessity led him down this wonderfully twisted statistical rabbit hole—a journey many of us know all too well. My path was similar, though admittedly less perilous (no developing Nazi countermeasures for me, just a lot of entrepreneurial research). You might call that “necessity-driven” career planning. This blog was born somewhere between a mid-career crisis and a statistics-induced existential reckoning. Beyond the personal stories and statistical musings, I’ll also share what I believe ails our field most: a chronic lack of clear thinking with data. Too often, researchers lean on formulas, models, and tests like checklists—missing the bigger picture and nuance that real insight demands. You’ll find this critique weaved through many posts as a common thread.

This blog is part therapy (mostly for me, not you) and part thematic exploration. It chronicles my personal journey and how it shaped the researcher I am today—take that for good or bad. As you read along, I hope you’ll find some of my experiences useful for reflecting on your own. Everything here is my personal opinion. Acknowledging that much of what passes for “knowing” in statistics is really just well-informed opinion is a crucial first step on the road to progress. I’m happy to help you get going — feel free to disagree, of course. Yes, I’m occasionally wrong, because being a scientist means rarely being absolutely certain but always being eager to learn when mistaken.