Is Data Science a Stressful Job? Here’s What It’s Like!


If you love maths, science, and programming, have great communication skills, and are a critical thinker, data science could be one of your ideal jobs. A lot has been said about this job, but what is the reality of being a data scientist? Is being one stressful?

Data Science can be a stressful job because it has its challenges. But whether it is truly a stressful job or not is pretty subjective, depending on the circumstances, working environment, and the project. People with a passion for the job enjoy it while others may experience undeniable stress.

In this article, we’ll outline what it’s like working as a data scientist. Let’s dive right in and have a closer look at the perks and challenges of a data science job. 

Important Sidenote: We interviewed 100+ data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!

The Positive Side of Being a Data Scientist

Being a data scientist means you have the most promising job in the U.S., according to LinkedIn’s 2019 report. This statistic in itself goes to show that there are a good number of perks that come with working as a data scientist.

Great Work-Life Balance

Yes, you read that right. Despite what many tend to think about data scientists being too busy and always bogged down with work and deadlines, this job actually offers a good work-life balance.

These are not just empty claims but actual feedback shared by data scientists on Glassdoor. Data science ranked third as the best job for work-life balance. 

Some of the reasons for this may be the fact that this job typically involves working on a project and creating solutions before moving on to the next one. Therefore, data science professionals can schedule their own time so long as they complete the projects and meet deadlines.

Of course, this also depends on the kind of deadlines set by the employer or client; if it’s too strict, it may not allow for much free time away from work. But for passionate data scientists, this doesn’t seem to be a big issue because they enjoy what they do.

Handsome Payoff

Data scientist has been ranked as one of the best jobs in 2020 by Glassdoor. This is based on specific parameters, one of them being the payment. The median base salary of a data scientist is $107,801. This makes it quite a lucrative career choice. 

What is more, the job growth rate of data scientists between 2018 and 2028 is projected to be 16% by the Bureau of Labor Statistics. This is thrice the growth rate of the overall job market. Therefore, this field is only getting better and more in demand. 

Versatility

Data is the lifeblood of a business; therefore, the roles of a data scientist, which include data collection, analysis, strategizing, and managing, can be carried out in a variety of industries.

Data scientists can work in different niche industries, including healthcare, education, marketing, consulting, etc. You can also work in government institutions, non-governmental, or non-profit organizations; the choice is yours. This versatility is one of the refreshing advantages of working at this job. 

The freedom to work in any industry allows for one to choose a niche they are most interested in or explore different industries until they come up with their most preferred. 

Fun and Exciting Work

This goes for those who are passionate about and truly enjoy data science. It’s exciting to be able to gather data and after analyzing it, come up with solutions that steer the way for institutions and businesses, both big and small.

Coming up with different algorithms, working with numbers, coding, programming, and solving real-life problems using data can be a fun, unique, and refreshing experience every time. No one day is the same as the other, and that’s part of what makes this job quite exciting.

Challenges of Being a Data Scientist

Even with all the perks of being a data scientist, there are real challenges that can make this job stressful or frustrating. Let’s have a look at what causes stress in data science jobs.

Intense Data Mining

Data scientists spend a huge part of their working time collecting data. If you’re working in/for a big enterprise, you have to ask all the different departments to get relevant data. This can be quite tiring and draining. 

One of the reasons this task often becomes stressful is because of the thoroughness that is required to do data mining. Your calculations and conclusions will only be as accurate as the quality of the data you collect. 

If the data sources are unreliable, that can undermine your efforts, while lacking control over which sources are used by the company can be quite frustrating. 

Stressful Work Environment

The work environment of a data scientist can be quite stressful because of long working hours and a lonely environment. It’s strange to note that despite the multiple collaborations required between the data scientist and different departments, most of the time, data scientists work alone. 

Long working hours mostly come up when there are huge projects to complete and other deadlines to beat. 

Difficult Troubleshooting

Problem-solving is one of the essential skills that a data scientist should possess. But unfortunately, no matter how good one is at troubleshooting, there are those instances when you will still get stuck on an error. Try as you may, you are not able to get to the bottom of it. 

Another hiccup is having an algorithm that doesn’t work or a model that’s not improving. You may spend countless hours trying to investigate and discover where the problem is, but it’s no guarantee that you’ll get the solution. 

These obstacles experienced in the line of work can be quite frustrating and draining due to the sheer amount of effort put to work on them.

High-Performance Expectations

The responsibilities placed on the shoulders of a data scientist can be quite heavy. In assessing the data of a whole company, for example, one has to go through millions of transactions and customer information. The amount of data cleaning and analysis required can be draining.

What is more, the conclusions made have the potential to influence the course that the business will take. This means the expectations placed on data scientists are quite huge. There is also the pressure from within with data science professionals trying their best to ensure accurate and reliable data conclusions are made. 

High Competition 

Data science is an increasingly popular field. The demand for more professionals in this area is on the rise every year. 

Everyone seems to want to have a piece of this pie, especially due to the good salary and work flexibility. For this reason, competition has shot up, and to be able to stand out from the crowd, you now have to be extra good. This puts a lot of pressure on most professionals in this industry.

System-Wide Collaboration

Collaborating with companies, businesses, or other stakeholders is another aspect of a data science job that can be quite challenging. This is especially difficult for introverts.

Data scientists are expected to understand various perspectives from different stakeholders. What is more, it’s their responsibility to communicate their findings and conclusions to the employer or client. They need to explain the impact of the analysis to the business in a way that’s easy to understand. 

This, combined with the stresses of huge data collection and the need to understand different niche industries, can be a lot to take in and quite difficult to balance. 

Author’s Recommendations: Top Data Science Resources To Consider

Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.

  • DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
  • MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
  • Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.

Conclusion

There you have it, a look into the life of data scientists. As you can see, whether stressful or not, it all depends on your point of view. You can be so passionate about the job and be excited about the high payment, versatility, great work-life balance, and enjoy the fun tasks of being a data scientist.

On the other hand, the intense data collection process, difficult troubleshooting, stressful work environment, high competition, and system-wide collaboration can be causes of a lot of stress in this field of work.

BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed 100+ data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.

  1. Cain, Á. (2017, September 24). What it’s like to have the best job in America right now. Business Insider. https://www.businessinsider.com/what-its-like-to-be-a-data-scientist-best-job-in-america-2017-9?IR=T#why-data-scientists-have-the-best-job-1
  2. DataFlair Team. (2019, March 27). Pros and cons of data science – Why choose data science for your career – DataFlair. DataFlair. https://data-flair.training/blogs/pros-and-cons-of-data-science/
  3. Noodle. (n.d.). Noodle: The Smarter Way to Search for School. https://www.noodle.com/articles/the-pros-and-cons-of-becoming-a-data-scientist
  4. The perks of being a data scientist. (2020, February 24). Big Data Made Simple. https://bigdata-madesimple.com/the-perks-of-being-a-data-scientist/
  5. Why data science is so stressful. (2018, December 28). SAP Blogs | The Best Run Businesses Run SAP. https://blogs.sap.com/2018/12/28/why-data-science-is-so-stressful/

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Daisy

Daisy is the founder of DataScienceNerd.com. Passionate for the field of Data Science, she shares her learnings and experiences in this domain, with the hope to help other Data Science enthusiasts in their path down this incredible discipline.

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