Table of Contents

1. Introduction
2. What has stayed the same?
3. What is different?
4. Summary
5. References

Introduction

2020 has of course had a plethora of unfortunate events affecting nearly everyone. But how was the tech industry been affected, and more specifically, how has Data Science in 2020 been affected? Depending on where you live, which industry you work in, and what type of Data Scientist you are, these similarities and differences may or may not apply to you. Below, I will be discussing these effects and how it may still affect you for this rest of the year.

What has stayed the same?

Because Data Science is a part of the tech field most of the time (or the role itself does not nearly require as much in-person work compared to other jobs), there have been a few parts of the day-to-day job that have fortunately been able to stay the same without negative disruption. Here are the similarities or parts of the Data Science process that have stayed the same:

• Use of video conferencing

Of course, video conferencing is extremely common now, but in my personal experience, and known experiences from other close friends in the Data Science community, video conferencing has been prominent in most day-to-day work in the past already. At a few of my previous companies, it was required of me and our team to have several calls over video throughout the workweek, and even several calls per day. The reason for this communication was because while our team worked closely together in person, our stakeholders did not. Instead of driving 30 min up to an hour to the other offices that had different departments — more centered around business and non-technical focus, we would instead have a video conferencing call. That way, when we really were required this year to do this same method of working, it actually was not that big of a change from our previous day-to-day work.

• Cross-functional collaboration

Similar to what I stated above, both then and now, requires the collaboration of not just a Data Science team, but several other teams as well. Some examples are working with stakeholders in either Marketing, Business Analytics, Customer Service, and others. The same collaboration is prominent this year as well.

• Use of JIRA and other product management tools

As a way to collaborate with our stakeholders, we would use JIRA or other types of product management tools to communicate. We would create tickets and progress through them with sprint goals in mind. The same is true this year as well.

What is different?

As some of the day-to-day has stayed the same for Data Scientists, there has also been a significant change in everyday work for this year.

• Much more video conferencing

Whereas we were already performing video conferencing for a lot of our collaboration in Data Science, we have done on video conferencing for this year. At first, it was a little overwhelming, because you would have to learn the etiquette of communicating over video (trying not to interrupt but also participating when necessary). But now, it has become commonplace and expected, so it has been a difference that has slowly become normal.

• No more in-person work (for a lot of companies, not all)

Along with the above point, there is no in-person work. I even started my job this year completely remote. It was definitely a unique experience, but with each and every day, it becomes more normal.

This change has also prompted companies to ask if they need offices in the first place.

Whereas remote work sometimes had a negative conadation — laziness, less work, etc., it now has much more respect, and some companies are even seeing more progress.

• The hours you work

One of the more unique side effects of working remotely this year is not prescribing to your normal 9 am-5 pm work hours. Some days you can start a little bit later, but then you will find yourself working till 7 pm at your home office, just because you are not reminded of trying to avoid traffic and leaving at the normal, society-driven 5 pm cut-off work time. This can be a positive or negative effect depending on the person and company, of course.

• The new amount of time you get for working

One of the possible positives from above might be when you are home all day working, you may find yourself producing more results and researching more. The new amount of time you get for working can be a positive difference because you are no longer commuting to work for say, 30 minutes to 2 hours — where I live, and other bigger cities, traffic can feel like it tasks forever, and by the time you get to work, you would actually be exhausted, only to do it again when you left. So, a positive is being able to just jump into work after only being awake for a few minutes, and getting more work done, and perhaps being done with your remote work day at 3 pm instead of 5 pm.

Summary

As you can see, there are several key takeaways and points for what has stayed the same and what has changed in 2020 for Data Scientists. A lot of these points can also be applied to other carers and industries as well. To summarize, here are those key points:

Stayed the same:
Use of video conferencing
Cross-functional collaboration
Use of JIRA and other product management tools
Is now different:
Much more video conferencing
No more in-person work (for a lot of companies, not all)
The hours you work
The new amount of time you get for working

Thank you for reading! I hope you enjoyed my article and learned something new. Feel free to comment down below the experiences you have had in 2020 as a Data Scientist. What has stayed the same for you, and what has been different? Which changes do you dislike, and which do you like?

References

[1] Photo by Jude Beck on Unsplash, (2019)

[2] Photo by Gabriel Benois on Unsplash, (2020)

[3] Photo by Markus Spiske on Unsplash, (2017)