Data Science Journey Entry #11

It’s been a long weekend of exams, university catch up from a busy work-week and a couple of great and interesting conversations in terms of career chats surrounding a career in Data Science. I have two more to come tomorrow so it would be possibly to speak on these next week, but it’s fresh in my mind now. The first I spoke to worked as a Data Engineer on delivering Data Warehouse projects, and the second was a more traditional Data Scientist developing solutions to common work problems, specifically with logistics. Basically, this is exactly the kind of work that sparked an interest in me when I first came across the discipline a number of years ago. And so, it is comforting to become aware that it still has a rather similar impact.

I guess these conversations haven really helped me to crystallise exactly the type of work I want to do and what skills and abilities that I need to know in order to get there. But it does still feel like there is some missing information that I do not quite have. However, upon consideration this seems just to be due to a lack of exposure, and as I speak to more people in this space I’ll develop a stronger and stronger understanding. Furthermore, once I actually get a Data adjacent job the complexities of what is required will then become very, very clear to me.

So, in summary, I’m not concerned. It’s been good to speak to people. And insightful too. And nothing can really prepare me so much as actually beginning a job in that space. The trick now, is to be patient, focus on my learnings and progress and see what happens next.

Finally, the most obvious takeaway is the importance of coding skills. I suppose no big prize for guessing that, but really focusing on a strong capability in SQL and Python seems almost essential. And perhaps that piece of information hadn’t quite awoken in me yet. Now it has. And that’s going to be a big focus for me, just as a key skill that I’m always practising.

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