
Working in the Data Science field can often seem to require a lot of time being spent in front of a computer screen. Whether it’s learning new tools, developing your programming in Python and R, or staying up to date on research papers. And this doesn’t include the expectation of working on side projects, portfolios, or additional non-related data science tasks.
While this is all part of the data scientist’s life, it can sometimes have negative health impacts, both to your mental and physical health. Clinical research has shown that looking at screens for over 6 hours daily can worsen a person’s mood and lead to depression. Additionally, sitting down at a desk puts additional stress on your spine and spinal discs especially with poor posture.
So how do we avoid these negative effects?
Well, unfortunately, we cannot avoid them completely but we can do things to mitigate the risks and improve our overall Health and relationship with screen times. In this article, I’ll go over a couple of the things you can do.
Use Dark Mode
Nowadays, many platforms and software that data scientists use provide some sort of ‘dark’ mode setting. By default, most platforms display black text on white background. By switching to dark mode, often means it will display white text on a dark background.
Why would you want to do this besides the fact that "dark" looks cooler? The dark mode is supposed to reduce blue light exposure and help with the eye strain that comes with prolonged screen time. It also helps make it easier for you to quickly fall asleep if you are looking at the screens close to bedtime.
Whether you are using your internet browser, R Studio, or your favorite IDE, most of these platforms have the ability to easily change the theme to a dark setting.

Get A Standing Desk
If your space allows for it and you are physically capable, a standing desk is a great way to help negate the harmful effects of sitting down too much. This includes improving your mood and energy levels, reducing back pain, boosting productivity, and even lowering your risk of obesity and metabolic diseases that are often linked to sitting down for long.
And the great thing about most standing desks is that they are adjustable allowing you to change the height of the desk and screen as best suits your preference and comfort. It also makes it easy to alternate between sitting and standing which gives you a better balance while working at a screen for long consecutive hours.
Prioritize Exercise Time
Just as you prioritize time to do exploratory data analysis on a new dataset you’ve been given access to, putting time on your calendar (literally or figuratively) to exercise is also important. This could be as simple as getting up from your desk every hour to walk around or going for a short midday run. All that is important is that you take breaks and pursue some physical activity of your interest.
If you are really ambitious, treadmill desks can give you the best of both worlds.
Only Work on Side Projects You Actually Like
As data scientists, many times, we are looking to expand our portfolio or range of skillsets by taking on new projects for our portfolio that can showcase our mastery of a particular area.
This is especially relevant for junior data scientists or those still in academia who may need to rely heavily on their portfolio and project to land an industry job without professional experience. In those cases, you may take on specific side projects that you think will highlight a specific skill or domain focus that you believe employers are looking for.
Unfortunately, this often means spending additional hours outside of your daily job responsibilities or the classroom to work on these projects. Realistically, you may not always like working on those projects in your free time but are willing to do it to get to where you want to be.
My advice is to maintain that determination knowing your end goals. But when you do have that job or position you want, try to focus on side projects in your free time that you actually do enjoy. It will be that much more rewarding, motivating for you and your health will thank you!
Transition Work Offscreen When Possible
One of the most rewarding aspects of data science is that it is a rapidly growing and changing field. There is always new research on the most cutting-edge machine learning algorithms or improved uses of artificial intelligence. This means that most professionals and data scientists have an interest and are motivated to spend their free time outside of day-to-day activities to stay up to date whether it is through reading white papers or articles and tutorials which are often presented in digital form.
Instead of spending more time in front of your screen, one alternative to avoid additional hours is to print out research papers and read them. Not only does that reduce strain on your eyes but it’s a lot easier to highlight and take notes on the paper which can help with how effectively you absorb the information.
Additionally, instead of reading articles or other online materials regarding data science topics, you can read a published book on those topics.

Reduce Your Hours
This one is pretty simple. Don’t stay looking at your screen for long periods of time. Take breaks. Don’t do 50+ hour weeks at work.
If you’re working from home all day at your desk, step away from your computer every hour or so. Go walk around your home/backyard or go drink a cup of water from your refrigerator.
If you’re feeling pressure to meet a deadline or get a project done, reducing the amount of time you are working, and therefore looking at a screen, seems challenging. But one thing you can do is be more efficient with your time and reduce distractions allowing you to get more done with less time. If you haven’t heard of the Pareto principle, also known as the 80–20 rule, it says:
80–20 rule asserts that 80% of outcomes (or outputs) result from 20% of all causes (or inputs) for any given event.
In other words, 20% of the effort and time you put into a particular project or task results in 80% of the work done. That means the rest of the time spent isn’t contributing as much to the end result and therefore there is a ton of room to maximize your working efficiency and win back time away from your screen(s)!
Final Thoughts
Working in the data science domain can be a rewarding experience and your passion for it can drive you to spend a lot of time mastering your craft and skills. However, just like anything else in life, moderation and balance is key to having a healthy relationship with it. The most important thing is you and taking care of yourself. Keep to your working hours as best as possible and find ways to be more efficient and give yourself breaks or find healthier alternatives to work.
A career in data science is long, so take your time with it.
References
(1) – https://www.healthline.com/health/the-mental-health-effects-of-being-constantly-online
(2) – https://www.healthline.com/health/is-dark-mode-better-for-your-eyes