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Should You Consider Being a Data Scientist in 2021?

What are the pros and cons of a data science career?

It’s the start of a new year, new adventures, new events, and maybe a new career?

Here we are in 2021; you might be sitting there, unhappy with your current career and want to change it; you might be unsatisfied with the work you’ve been doing, with the financial aspects of your current job, or simply don’t feel challenged enough. Or, you’re maybe a student trying to decide what to do with your future, or you might be either.

Regardless of why or how you get here, you’re here, and you’re considering a career change or a career start. You look up online for jobs that pay well, are intellectually challenging and fulfilling. You come across different jobs, and Data Science job roles look intriguing and seem promising.

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Over the past couple of years, data science has maintained its position as one of the most promising and in-demand jobs, according to LinkedIn and CNBC. And as our data-dependency grows every passing day, I don’t forsee data science job roles to go anywhere, anytime soon.

But,

Choosing a career is a very complex decision; it’s not one that is easy to make. That’s why I thought to help you make this decision. This article is not intended to push towards data science careers or push you away from them, rather provide you with the facts you need to make your decision. After all, you know you the best.

Let’s get to it…

Advantages of having a career in data science

Well, let’s start with the pros of choosing a career in data science.

№1: It doesn’t require a degree

This is perhaps one of the most important pros for me. Many high-paying jobs require some college – or equivalent – degrees, which requires a long time and a lot of money. However, data science, contrary to what many people believe, doesn’t require a college degree.

To have a career in data science, you need to learn some core concepts and build as many projects as possible to show your competence. This means you can become a data scientist in a relatively short time with less money compared to college tuition.

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№2: It’s a well-paid field

Money matters and I would argue a lot. When you put in the effort, you expect to have an equally valuable return for your efforts. Money is one of the ways a job role is valued in the market.

Data science and many IT roles have a relatively high salary compared to other jobs. According to The University of Wisconsin, in 2020, the average salary for an entry-level data science role can be as high as 95,000$/year.

№3: It has versatile applications

Data science is a field with applications across many industries, including medicine, e-commerce, marketing, and more. Because of this wide range of applications, the field’s demand is not decreasing in the near future.

Furthermore, the continuous advances in the field will only widen its application range even further. I must say that data science applications in the various fields are not just numerous; it’s also very essential and critical to the continuum of other fields.

№4: It’s one of the fields with high gender balance

As a woman in tech, one of the pros of data science is that it has less gender gap than other computing and engineering fields. In 2019, the ratio of male to female data scientists was 7-to-3, which is not great, but still better than other job sectors.

With the need to diversify and include more women in the field, I can only hope that the ratio will become more balanced in the upcoming years, especially with more capable women joining the field.

№5: It can be done remotely

When COVID hit us all hard last year, we came to value job roles that can be done remotely. That can be equally effective regardless of your physical location. Such jobs opened up more doors to international collaboration and lead to interesting results.

Data science is probably, like most computing fields, can be done remotely, which is one huge advantage, especially considering the situation we live in. We can be with our loved ones without the need to sacrifice our career prospects.

№6: It’s a challenging field

We all – I hope – love to be intellectually challenged. Especially if you look into a field like data science, data science can be quite challenging; it requires a constant stage of self-development and continuous learning to be considered good in the field.

You will also need to study various aspects of other fields to be able to perform your job correctly, which represents another learning opportunity for data scientists.

Disadvantages of a career in data science

To be fair, we also need to consider some of the downsides of choosing a data science career.

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№1: Most job roles are vague

Data science is one of the vaguest terms you’ll ever come across. There is no solid, fixed definition of what a data scientist’s job responsibilities should be. They change based on the company or the project or sometimes the person themself.

Because of this vagueness, knowing what you’re getting into when applying for a data science role or when getting into the field to start with can be quite challenging, which leads us to the next con.

№2: Getting a job is not easy

Although the demand for a data scientist is not low, and the prospect for job opportunities is promising. Most new data scientists find it challenging to get a data science role!

Why? The vagueness of the term causes problems for both the companies hiring and the people applying for the job. Most companies don’t know what they are looking for. Hence they provide false job requirements. That leads to the people applying for the wrong positions.

№3: You need to acquire cross-fields expertise

Data science is a very interdisciplinary field. To be a data scientist, you need to obtain knowledge of math, Programming, statistics, science communication, marketing, and business. And based on specific projects, you might need even more knowledge.

Although that provides an intellectual challenge, sometimes, needing to obtain all this knowledge in a short amount of time is not always easy to do and might get quite stressful.

№4: It’s impossible to master

The trick to master a very active field like data science is that you need to be continuously up-to-date with recent algorithms, research, and findings. That can get overwhelming very fast.

Data science is an ongoing field, which means it is never finished. As long as we have data, we’ll find better ways to read it, collect it, and analyze it. So, mastering this field is quite impossible.

№5: The ethical problems of data privacy

Data science is all about the data. It a story being told with numbers and information. And just as with any other field involving collecting and handling data, you will have to deal with data privacy’s ethical issues.

All data science projects are data-driven. Data scientists are trained to make decisions based on the data provided to them; during this process, sometimes they will go through data that the users didn’t allow to be viewed. That will cause privacy issues that are often complex to solve.

Making the decision

So, I presented you with some of the pros and cons of choosing data science as a career. What decision should you make now?

Every career option will have the good and the bad; that’s just life. It is up to us to evaluate our ability to put up with the bad for the good. For me, the advantages of becoming a data scientist over-weighted the cons, and that’s how I made my decision. And that’s how you should approach yours.

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Takeaways

Data science is one of the most glamorous job prospects right now. Not just now, it has been for a while now, and it will continue for the foreseeable future. Hence, data science may seem like a promising and intriguing option for many considering a career change.

With the kick of a new year, would you consider a career in data science? The best way to make the decision is to look at both the good side and the bad sides of choosing data science, and then, based on your values, your goals, and your personality, you can make the decision.

In this article, I presented you with some of the advantages and disadvantages of data science careers. Hoping that I gave you enough materials to make your decision-making process easier.

Good luck.


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