Have you ever searched online for a baby shower gift, and then the ads on your computer the next day are all for baby stuff? What about purchasing something on Amazon, only to have it recommend more products like it to you?

These intuitive (and sometimes unnerving!) innovations are thanks to data science. Careers in data science and analytics are in high demand because of the intuitive nature of our technology nowadays.

Check out these 11 data science careers that are shaping the future!

What Is Data Science?

First and foremost, we have to nail down what data science is. The field is wide and still expanding, so its definition is broad: using science, analysis, and algorithms to interpret data.

The easiest examples to understand are those we see every day: Instagram’s algorithm that sorts what posts you should see first, Apple’s facial recognition software, and Facebook’s cookies that create ad content. That kind of information analysis is exactly what data science is all about.

What Do Data Scientists Do?

The term “Data Scientist” is just as broad as the field itself. It’s an umbrella term and many different careers fall under it.

It means different things to different companies, so don’t assume that there are clear and obvious separations between “Data Scientist” and “Data Engineer.” If you’re hired by a company to be a data engineer, you can expect to also do some things that a “Data Scientist” or “Data Architect” might do.

Overall, data scientists are the people who build the processes and algorithms to collect information, then analyze the information in a way helpful to their specific company. The way you’d analyze the data would differ if you were an Amazon employee vs. an Apple employee.

1. Enterprise Architect

Think of an Enterprise Architect as the director of data science at a company. He or she is in charge of creating and directing the company’s overall analytical approach: What data are they looking for? How will they collect it? In what ways will they analyze and interpret it? What will they then do with it?

They also work to mold the company’s data science, goals, and IT systems into one cohesive flow. It should all work together toward the company’s purpose, so the Enterprise Architect builds systems and changes things where needed.

If you’re interested in becoming an Enterprise Architect, you can take data science courses online.

Average base pay salary: ~$139,000

2. Data Scientist

Like we said earlier, “Data Scientist” is a loose term. It can be used as an umbrella to describe all of these careers but it’s also a career in and of itself. Different companies require different tasks of their Data Scientist.

They’re generally in charge of collecting and using data to meet their company’s needs and goals. Machine learning is part of that. Ideally, the framework they build and reinforce will lead to strong, reliable overall analytics.

Average base pay salary: ~$113,000

3. Machine Learning Scientist

Many companies use “Machine Learning Scientist” and “Machine Learning Engineer” interchangeably. Here we’ll break them down separately.

If you’re into really understanding computers, coding, artificial intelligence, natural language processing, and other exciting, futuristic things like that, machine learning science is for you!

Don’t know what “machine learning” is? It’s basically how computers think, and how they use the information they have – like algorithms and statistical models – to then do what they’re supposed to do.

A Machine Learning Scientist would be an expert in machine learning, computer science, and even artificial intelligence. Can you see why this kind of career is shaping the future?

Plus, they are few and far between, so they’re extremely valuable in the workforce. You’d be easily marketable and it probably wouldn’t be hard to find a job.

Average salary range: $79,483 – $118,502

4. Machine Learning Engineer

Machine Learning Engineers are computer programmers. They deeply understand computer systems and computer language.

They then engineer machines to perform whatever task their company needs. This requires building programs that direct the machines. It’s all very involved and very smart, so not too many people can do it.

If this field of study and work speaks to you, jump on it now! Many companies around the world desperately need good Machine Learning Engineers.

Average salary: ~$112,000

5. Data Architect

Data Architects range in position based on experience and expertise. For example, a “Senior Data Architect” job opening would offer a greater base pay salary than a “Junior” or first-time Data Architect. As always, experience is invaluable to employers!

Data Architects build their company’s database. They design, create, launch, and maintain the overall database framework, or “architecture,” which will best serve the company.

They decide on the systems the company uses to store and manage data. For example, there are multiple medical record systems available. A Data Architect would decide which one their specific medical office will use, based on compatibility with the database architecture and the company’s needs.

Average base pay salary: ~123,000

6. Applications Architect

An Applications Architect creates the actual applications on computers. Does your company use Slack to communicate? An Applications Architect (or a team of them) built that system!

If you want to be an Applications Architect, you take courses to thoroughly understand the anatomy of applications and software, and how to improve upon them. With building a new computer application, you’d have to create a prototype, test it, solve problems, and train others how to use it.

If a company wants their very own computer application that all their employees use, they hire an Applications Architect. Can you see now why this position is in such demand?

Average salary: ~$109,000

7. Infrastructure Architect

Think of the Infrastructure Architect as the improver of a company’s data system. They analyze the database, applications, and software for failures in security or efficiency.

They compare what’s being done to the goals of the company: Do they line up? Is the current hardware best serving the company? Does the operating system need to be updated or changed?

As such, the Infrastructure Architect is in charge of how well the overall computer system is working with and for the company. If there were problems or insufficiencies there, the company would come to you!

Average salary: ~137,000

8. Statistician

You can do a lot with a stats degree. You can perform valuable statistical analyses for any kind of company, anywhere in the world. Every single place needs a statistician!

As a statistician to a company, your job is to gather data, interpret it, and then present it in a way that’s totally understandable to a non-statistician. The purpose is to identify trends in the information – for example, that certain shoe sales spiked after a celebrity posted a picture wearing them.

Then you’d use that information to make predictions, which the company would count on depending on how sure they were. Making predictions and acting on their surety is a huge part of the value of statistics.

Average salary: ~$84,000

9. Data Engineer

A Data Engineer is similar to a Data Architect and Data Scientist. They create and maintain database architectures and frameworks.

They focus on making and working on big-picture, large-scale computer processes, rather than day-to-day, small applications. As a Data Engineer, you need solid knowledge of and experience in database systems, data modeling, and processing languages.

You implement new computer systems, create and maintain data storage, and do plenty of programming. Educational and experiential background in computer programming is crucial.

Average base pay salary: $85,000

10. Business Intelligence Developer

Business Intelligence (B.I.) Developers are all about IT. They’re supposed to implement the best and most efficient software possible for their company.

When you have issues with your computer at work, you call the IT team. The B.I. Developer works closely with the IT team. The B.I. Developer might not answer the call and come down to physically fix your computer, but they work to identify IT issues or lapses.

Average base pay salary: ~$90,000

11. Data Analyst

Of course, with any computer position, the job description (and salary) totally depend on the industry. Whether it’s the medical field, sales, a tech company, or a social media platform, they all need Data Analysts.

As the Data Analyst at a company, you use statistics to look at data. After analyzing and interpreting the data, you make sure everything is up to speed – are the programs and systems as efficient and optimized as they can be?

Average salary across the U.S.: ~$65,000

Data Science Careers Are the Future – Get On Board Now!

Data science careers really are the future because data science is so valuable, crucial, and in-demand! Countless companies wouldn’t be successful without utilizing data science.

Imagine the difference in Amazon’s sales if they didn’t analyze users’ browsing and buying! They wouldn’t know what to offer you next, which they’d lose massive amounts of potential business.

If you’re interested in technology and careers, check out other articles. You’ll find valuable information and news on current events. Don’t fall behind: staying up to speed with the world is key!