Is Data Science a Good Career Choice in 2024?

Our modern era is defined by data. Did you skip a song in your music streaming app? Data point. When did you skip it? Another data point. Did you keep listening to the next song? One more data point. And that’s just one tiny example.

So in this data-filled environment, it’s easy to see why data science is getting so much buzz. But should you become a data scientist? Are data scientists still in demand? Let’s dive into why we think data science is one of the best paths to pursue in 2024.

What is data science?

First of all, it’s useful to get on the same page on what we’re talking about. So here’s a quick definition:

What does a data scientist do?

Naturally, a data science job will vary based on numerous factors such as industry, team, seniority, and more. But, in general, data scientist jobs_{What Do Data Scientists Do?} orbit a core of applying programming skills, mathematical know-how, and business acumen to uncover trends in data. Day-to-day, they’ll find themselves cleaning up data, performing data analysis, writing algorithms, creating data visualizations and narratives, and reporting findings to colleagues and company leaders. 

Because data scientist roles are in a rapidly growing field, there’s a lot of noise around them. Often, it can be hard to differentiate data scientists from data analysts, who are likewise hard to untangle from business intelligence analysts.

They all work with data, but in the most basic sense, data scientist jobs focus on applying math and programming. They’re about building algorithms, and they work closely with software engineers. Think of the daily work of a data scientist as an overlap of data and coding.

Why is data science important?

This is the right question to ask, and it’s here that we get into why we think data science is such a good field right now.

For example, healthcare is awash in data, but without professionals who can make sense of these mountains of information, it’s useless. Just take one of Google’s data science tools powered by artificial intelligence: LYNA. It can identify a specific type of cancer with 99% accuracy, and it can even spot minute cells prone to metastasis, something that a human pathologist would struggle to replicate. So in one sense, data science is important because it can help save lives.

And while that might be enough to show how important data science is, we’ve got one more example: data science can help us make wiser environmental decisions. By taking in and processing mind-boggling amounts of data, Destination Earth, an algorithm currently in development in the EU, is generating a digital twin to our own earth. This model will be able to predict the ecological outcomes of policy decisions. And that can help lawmakers shape even seemingly innocuous decisions to make sure we minimize our harmful environmental impact.

So why study data science? Because with it, you can improve the world. In fact, one of our grads_{Data Science as the Smart Investment: Jacques Diambra Odi’s TripleTen Story} even worked on a data science project that can help locate people after natural disasters.

Is data science in demand?

In one word: yes. The demand for data scientists is so high that, according to the World Data Science Initiative, around 80% of firms are focused on building robust in-house data practices. So you can see that the job market for data scientists is hot, and demand for data skills isn’t just reserved to the tech industry, either. Throughout industries, a number of jobs are now opening for people with skills in data science.

For example, one of our grads_{How an Immigrant Landed a Career in the US: Evgeniia Unzhakova’s TripleTen Story} is using her big data skills in education. Another_{Revitalizing a Promising Career: Jordan Wilheim’s TripleTen Story} is helping sequence DNA, RNA, and other complex proteins. So even outside of the traditional data science paths, you can find a great data science job.

The future outlook for data science

Throughout professions focused on data — data analysts, data engineers, data scientists — the job outlook is rosy. In fact, the U.S. Bureau of Labor Statistics estimates that data scientist employment will grow by 35% by 2032, far exceeding the average of all occupations, which sits at 3%.

So you might be wondering: why is data science a growing career field? Well, it really comes down to a few things.

After all, data scientists are going to be the ones responsible for crafting, training, and honing these algorithms.

But, as we’ve discussed, this will not be limited to tech. As our landscape becomes increasingly defined by data, more people will be needed to wrangle and do something useful with that data. So, in short, data science is a good career if you’re looking to be employable far into the future.

The pros and cons of data science

If you’ve gotten all the way down here, you might be thinking it all sounds too good to be true. And while we are indeed excited about data science careers and think they are good paths to choose, nothing’s perfect. So let’s talk about some pros we haven’t touched on yet and bring up the main cons.

Pros:

1. Compensation

Data scientists are some of the highest paid workers in tech. If we look at our Outcomes Report, we see that our Data Science Bootcamp grads earn the highest median salary. And just doing a quick search on Indeed, we find that the average base salary for data scientists is, as of the writing of this article, $123,696.

But notice that we said compensation and not salary. Once you consider other payment approaches often implemented, that number can skyrocket. Companies can offer additional options such as variable pay, by which you get extra compensation based on sales or personal performance, bonuses based on the company’s growth, or even stock in the company. Because data scientists are in such high demand, compensation is likewise quite impressive.

2. Innovation

As we mentioned above, the next wave of tech is likely to be shaped by artificial intelligence and machine learning. These are the exact fields in which data science is crucial. So not only does this mean people with skills in these fields will be in high demand, it also means that they will be shaping what our future looks like. Some of the most exciting frontiers in tech are being explored and expanded by data scientists.

3. Work in harmony with your values

Projects in data science are doing real, measurable good for humanity. Skills in data science will allow you to align your work with the causes that matter to you. If you’re passionate about reducing humanity’s impact on climate change, data science is for you. If you want to reduce food waste and help with the proper distribution of resources, data science is for you. If you want to develop algorithms that can help diagnose illness earlier and get patients proper treatment before their conditions get out of hand, data science is for you. And there are so many more examples. Skills in data science will help you play an active role in initiatives that move you.

Cons:

1. Relatively high barrier to entry

Data science is a skill-intensive field. You’re going to need a wealth of abilities_{The Top Data Science Skills for 2024} in programming languages, math, and other profession-specific tools before you can reasonably expect to land an entry-level job in data science.

Getting those skills is eminently possible, but depending on the path you choose, it can seem like too long a path to tread. For example, people often assume that they need a degree in data science, and so they undertake long, arduous journeys toward getting certified in data science without asking themselves, “Is a data science degree worth it?” After all, spending four years getting a degree might not be worth the investment when you can get the same skills in other data science programs.

2. Increased scrutiny in terms of ethics and privacy

Data scientists, as the title implies, handle tons of data. That means they’re stewards of information that is remarkably sensitive as a matter of course. Because of that, they have to follow regulations at the federal, state, and even down to the company level so that all information that can identify a user is handled ethically and securely.

Data scientists need to stay up to date on these rules and laws as well as on the tools that can protect data from bad actors. This requires that they regularly upskill on cybersecurity protocols and keep an eye on data privacy regulations. But, on the upside, once you’re out in the world and working as a data scientist, good companies will prioritize your continual education and training.

3. Pressure

We often get the question, “Is data science a demanding career?” The honest, if simplified, answer is: yes. But it’s just like any other profession in which you’re doing high-impact work. Say you’re developing an algorithm to differentiate between two nearly identical diseases that have radically different treatment regimens. That algorithm better get things right.

Study data science at TripleTen

There are numerous ways to find success in the field. Data science degrees can give you the theoretical background you need, and sure, there are merits to going for a master’s degree in computer science, but if you want the quick and guaranteed way to land a job in data science, there’s no better bet than a bootcamp. 

TripleTen will teach you the in-demand skills to ensure you thrive in your first data science job, coach you to ace your interview, and set you up so that when you graduate, you already have an impressive portfolio to show recruiters.

Check out what our Data Science Bootcamp can do for you, and dive into our student stories to hear how people just like you have found success in tech.