Data Science in 2020

Data Science in 2020

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.

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.

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