How to Keep on Developing as a Data Scientist | by Eryk Lewinson | Apr, 2024

A few practical tips on how to keep on learning during your daily job

While I know it might sound like a cliché, being a data scientist often involves having the mentality of a lifelong learner. The field is developing so quickly that it takes time and lots of effort to stay up to date with the latest developments, whether it’s the state-of-the-art ML model, a new data manipulation library, or a just-released arXiv paper you’d love to implement. No wonder so many of us (myself included) suffer from imposter syndrome.

And while nowadays there are many opportunities to learn, our most precious resource is time. We can’t (or at least shouldn’t) spend most of our waking hours working and learning, as we would risk burning out quite quickly. So that’s why in this article, I would like to focus on the development possibilities during your 9 to 5 (or any other time range that applies to you).

I know that each company is different, and there is a high chance that you might already employ some of the things I mentioned here. And that’s great! From my side, I’d consider this a success if you find at least one new idea on how to keep learning.

The tips I will share in this article are based on my own experience so far and on things that I have heard from my friends and colleagues working in the industry. It is likely that some of these might be difficult to pull off in some companies. But I do believe that it always makes sense to try and you (and your managers) might be really surprised about the positive outcome!

Maximize the learning while working on your regular projects

While this tip might not be anything groundbreaking, you will hopefully continue to learn a lot while working on your regular projects at work. After all, that will be the majority of your workweeks. My advice here would be to make the best use of that time. Here are some ideas:

• Try exploring new ideas for your projects, such as using new models, approaches, or tools.
• Research what other companies are doing to solve similar problems.