Picking your professional path

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This at it’s core, is an optimization problem. How do you allocate the scarce resource of your professional effort? You can’t solve an optimization problem until your optimization criterion is very precisely stated. In other words, what do you want more than anything else?

On the surface, it may appear that technical impact, business impact, and social impact go together. That wealth and intellect can be built at the same time. That fame and academic reputation are all different parts of the same thing. And that peace and companionship and personal satisfaction accompany them. But in my experience, this is not often the case. A great many professional decisions are between what you want and what you want more.

Knowing what you want most can sometimes be the hardest part. I once told a friend about an algorithm I was working on. He asked if I could magically have one of two things, would I rather a) have the algorithm be widely adopted or b) get recognized for it? It was a great exercise prioritization. Did I want to make something I am deeply proud of? Did I want other people to think that I’m smart? Did I want to be wealthy? Of course, there’s nothing wrong with wanting all of the above, but there is very likely a time when you get to choose one over the others. When that time comes which will it be?

  • I’m curious about machines that appear to think, especially machines that move. I want to know how every part of them works. I want to try out my own ideas to make them better. This has captivated me since I was six years old.
  • I can best do this at work as an individual contributor. Management roles would prevent me from being immersed in the technical work. I’ve avoided them.
  • When choosing between work that is likely to gather attention and big bonuses and work that I find technically intriguing, I’ll lean toward intriguing.
  • When I hear chatter about a hot new subfield of AI, I take deep breaths, calm my FOMO, and turn back to my project on a thing that I’m curious about and feel satisfaction from.
  • I say no to a lot of invitations to speak or write or collaborate. Many of them are amazing but not quite worth all the time away from my curiosity driven work.
  • I invest time in sharing what I learn online. I’m so excited by understanding something new that I feel compelled to show others how cool it is. I want to mark the path to the place I found. Selfishly, explaining ideas helps me learn them on a deeper level too.

part of Course 121 Navigating a Data Science Career

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