Before grad school, I lived in Beijing. I had a job offer to be the guy-on-the-ground for a fashion company’s manufacturing outfit in China. I was excited about it. It was the era of Kickstarter entrepreneurship, and I saw this as a sure pathway to crushing it on Shopify.I gave it up and returned to the US for that Ph.D. student life.
I pivoted because I knew I wanted to be a numbers guy. I wanted it like art students want to be artists. Which is to say, I wasn’t thinking about money and a career. I figured I can always find another gig, but the window to do the Ph.D. thing was closing. I would regret it if I didn’t do it.
It was a culture shock. Going for a Ph.D. is signing up for a paper-writing indenture.
Nobody respected or cared about my accomplishments in business or entrepreneurship. I remember talking about my enterprise sales experience to my adviser, and she looked at me like I had just sharted. I was merely an engine for creating research. Talking about such things meant I was not focused on research.I still loved it. Nowadays, aside from my work at an AI SaaS startup, I teach at Northeastern University’s CS school. Most of my students are in a master’s program in data science. Most of them are NOT like I was. They have a specific career and financial outcome in mind, and they are paying premium tuition to get it. They could care less about the craft.
It’s not just graduate students. Most data science/machine learning people I meet in tech, including Ph.D. holders, are mercenaries, not missionaries. They either work hard to position themselves for more prestige or wealth within their organizations (often battling depression and burnout). Or they do the precise amount of work that their manager expects and not a bit more, utterly lacking spiritual or intellectual investment in their work, deriving all meaning from life outside of their job.
Admittedly, people working in academia are a bit different, but the problems of rat racing, prestige signaling, and spiritual disconnection in academic settings are a whole other can of worms.
I’m not making a normative argument. I’m not saying my journey is the best. I’m not claiming any superiority. I’m not saying my way of think leads to living a better life.
I’m saying I feel alone in this. I suppose I wish I met more people who think like me.
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I'm a bit late to the conversation. I am certainly not into prestige or wealth as the goal, but on attaining a full understanding of the problem and driving to efficient and effective solutions. That is why I share an interest in causal inference; understanding what is driving results is the only means of truly solving problems. Solving problems is all about intervention. Evaluating one's actions is all about counterfactuals.
This quote from Johannes Kepler, the first person to mathematically understand the motions of the planets -- and perhaps the first Data Scientist -- inspires the hell out of me:
“The roads by which men arrive at their insights into celestial matters seem to me almost as worthy of wonder as those matters in themselves.”
To me, those "roads" are the mathematical methods of data science.
Exploring those roads is all I want to do. We are what we are.
For the record, this makes data science/machine learning people exactly like everyone else in life.