I have been to the Data Conference this April in Moscow. It lasted for 2 days, and I can honestly say I heard more unfamiliar words than I ever expected to. I wrote them down anyway—some of them without knowing whether or not I will learn their meaning.
I’m not going to unpack all of it here, but I want to highlight a few things that struck me as meaningful, especially where I am right now on my learning journey.
What Makes a Good Data Scientist?
Here are a few insights I wrote down during the talks:
- Read the literature. Be aware, so to speak.
- Simplify until it can’t be simplified anymore. If you can explain it simply, you understand it.
- Modify how you solve problems. Be flexible, not formulaic. Try out and adjust.
- Discuss. New ideas are born in conversation.
- Theorize. And if someone gives you a theory? Test it.
- Write. Science is always a collective effort—and writing is how your thinking contributes to that. It also helps to learn to communicate thought in a clear and succint way.
Topics I Want to Explore Deeper
The conference gave me more than just a long list of unknown terms—it gave me the overall feeling of the field and possible directions to explore, listening to the variety of what’s been going on for the last years. Here’s what caught my attention:
- Graphs. I guess it is something about connecting the dots. I read about it, but still have no idea how it may be applied.
- LLMs (Large Language Models). I’ve heard them discussed so often—but how did they come to be?
- Integer Linear Programming. I have no idea what this means. But I want to find out. (Honestly, doesn’t it sound beautiful?)
Also, there was a question about P = mp. I HAVE to know what this is about.
All in all, I got to see really intelligent people who speak about all this stuff and understand it. Isn’t it amazing?! :)
