When my son asks my brother a career question

I used to write about this brother a lot. Now he’s older and he’s giving career advice to my son. Here’s what Z wrote my brother: Here’s a copy of my resume. Can you please give me feedback and also, I can’t decide between data analyst,  AI engineering, or AI research. Everyone is applying to every AI job so I think I should probably do data analyst. What is your opinion?

1 reply
  1. Penelope
    Penelope says:

    This is from my brother/ Z’s uncle.

    I understand that you want to climb the corporate ladder. That’s what I do. And I would choose it again. I’m trying to come up with a way to pass on my wisdom on this, but can’t figure out how to make it short and pithy. So it got long. Feel free to run it through chatgpt to summarize.

    Basically, when there is mania about something in tech, which there nearly always is, you have to figure out if it’s real or not. if it is, even though everyone else is running to it, and many of them are morons and/or grifters, you still have to run to it also if you want to be at the top. The best indicator I can think of for something being “real” is that all the big tech companies are going after it – think of the internet in 1998 or mobile in 2005 or cloud computing in 2010. Contrast that with Bitcoin or NFTs or the Metaverse, of which maybe 1 or 2 of the big tech companies are dabbling in, but no one is going all-in (despite Meta’s name!). AI is clearly the former.

    So while data analysis / data science / machine learning is tried and true, and was hot 5-10 years ago, it has always been very broad (for every machine learning engineer, there’s 5 data analysts analyzing accounts payable spreadsheets) and so hard to clearly standout. And it’s passe/not revolutionary technology like the other examples. Maybe a good time for the alleged Wayne Gretzky quote – “skate where the puck is going”. It’s AI, not data analysis.

    It will be hard to stand out in AI (harder, in fact, than data), because it’s so competitive, but you have early achievements on your resume that suggest you’re special. So people will consider you might be legit / give you a chance. You won’t be confused for a LinkedIn AI influencer, that’s for sure.

    Final analogy: just like in cello, in corporate America as soon as you don’t shoot for the top at a given stage in your career, you are pretty much precluded from getting to the top. There can be good reasons to make the decision to take a step down, but you should be deliberate about it, and know what you’re getting for the trade. In my own case, I didn’t think I was giving up being CEO of a big company when I left [big famous company] – I thought of it as an opportunity to accelerate my career at [smaller unknown company]. But that wasn’t a good step for me and I had to course correct. This is to say I don’t think data accelerates your career, and at this stage, if you plan on climbing the corporate ladder, you have to think about the best ways to accelerate your career.

    I guess my final point is go after an AI job. At a great company. But — and I know this contradicts everything I just said — If you can get a data / machine learning job at Apple, Microsoft, Facebook (or somewhere like that) you should take it.

    I’m glad you liked the helicopter joke. I was quite proud of it, but mildly concerned you’d be offended.

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