The Benefits of a Career in Data Science

Interest in careers in data science is growing. This is a career that offers a lot and that seems to be getting more and more attractive as time passes. This is primarily because of the benefits already present for data scientists and those coming in the future.

If you’re considering a career in data science, you may be wondering what these benefits are. Keep reading to explore a few of the most significant benefits out there.

High Demand and Low Supply

Everyone wants to have a job that is in demand. Jobs like these offer a level of safety and comfort. People in these positions don’t have to worry about suddenly losing their job since they know they are a valuable commodity. This gives them better peace of mind throughout the year, especially during tough economic times.

Demand for data scientists is not only high, but it is also growing. The employment of data scientists as a whole is estimated to grow 36 percent from 2021 to 2031. This is a massive increase that significantly outpaces most other careers.

The lack of a large supply of data scientists further enhances these benefits. This makes competition for positions less stressful and increases job security.

Great Compensation

Being in demand has a few perks. The law of supply and demand suggests that careers that are in demand will be compensated better. This is even more true if there are not many workers in this field. With these careers, employers need to offer more in order to pull in the limited number of workers. As data scientists are in demand, their compensation conforms to this rule.

Data scientists generally make anywhere from $85,000 – $170,000. This depends a lot on the level of experience the person has. Data scientists with degrees or who have gained experience through coding bootcamps can expect to make more than those without these accolades.

Positions are All Around

Another advantage of the high demand for data science jobs is the fact that they are located all around the world. There are data science positions in nearly every major city and many smaller ones as well. Plus, more and more work-from-home and hybrid positions are opening up.

All of this makes getting a data science job easier. With other careers, you may have to move large distances to get the job you want. However, with data science, there is a high likelihood that a city nearby has an open position that will work for you.

Or, if you’re looking to make a change, you can go for the opposite. Pick the city you want to live in and look for a career there. In this way, data science can be your springboard into a new life.

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Positive Work/Life Balance

Many jobs, especially those in technology, have a chaotic work/life balance. They require a lot of time out of one’s schedule, leaving little time left over. They can even intrude in weird ways, as some IT positions get emails at all times of the day that need to be answered quickly.

Luckily, data scientists do not have this problem. Most data scientists work normal hours during a normal work week. This means they will work regular hours on the weekdays and have off on the weekends.

However, some data scientists have it even better. Some data scientists get jobs that have hours that are entirely flexible as long as they accomplish their tasks. Others are able to work from home and make their own schedule. Both of these situations are particularly attractive in the modern world.

Woman drinking a hot drink and reading a book

Building Connections

Some technology careers are a bit isolated. Certain career paths put workers in contact with people on the same path and don’t really allow them to branch out much.

Data science isn’t a career that exists in isolation. In fact, data science tends to head in the opposite direction of this trend and has workers interacting with people from all over. In particular, data scientists often end up working with some of the higher-ups in a company.

This is a huge advantage as it gives data scientists plenty of time to network. Networking is a big part of being successful in any career. Doing so creates connections that provide all sorts of benefits. Being clued in on potential jobs, getting promotions, and building a positive reputation all come through networking.

Work With Prestigious Companies

Building connections is even better when it takes place within a well-respected company. This is an advantage for data scientists because many prestigious companies are constantly on the lookout for data scientists.

Apple, Google, Amazon, Facebook, and Microsoft are some of the biggest companies in the world and, together, are worth over $5 trillion. Positions at these companies are highly respected, and many consider a position there to be the ultimate sign you’ve “made it” in the technology industry. These companies also happen to be companies that heavily rely on data scientists.

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Potential for Promotion

Getting a job in data science often means starting at an entry-level position. However, unlike other fields, employees in data science don’t stay in these positions for their entire careers. Instead, they work their way up the ladder.

A data scientist may end up taking on more responsibility as a senior data scientist. Or, they may move on to a management position. They may also leverage their experience to get any number of other positions.

In other cases, moving up may mean changing companies. Oftentimes, when a data scientist has outgrown the company they currently work for, they take on a similar position at a larger company. In these cases, they typically end up making more while simultaneously increasing the value of their work. Eventually, these company changes may result in a data scientist working for one of the massive companies mentioned earlier.

Man in a suit happily looking at his phone

The Benefits of Data Science

A career in data science has the potential to be seriously beneficial. These careers are often in demand, comfortable, come with great salaries, and have a lot of potential. Because of this, anyone with the skills to get a career in data science should consider doing so.