Data is the future. From automakers to social media platforms, every business that you interact with would like your data. What they all understand is that your data is one of the most valuable assets they can obtain. Why? Because your personal data tells a major story about who you are, what you like, and what you purchase.

It is truly incredible to see the wide array of uses that data has in our lives. Much of the data collection process occurs behind the scenes. However, there are people using data science to collect vital details about every customer.

The Projected Future for the Data Science Industry
It is impossible to predict the future completely accurately. However, there are certain organizations and government agencies that try to forecast certain economic fields. The U.S. Bureau of Labor Statistics is one highly trusted government agency that collects data and reviews it to try to detect patterns that may be useful for predicting where a certain industry is likely headed. A report from the agency states the following:

Employment of mathematical science occupations is projected to grow 27.9 percent from 2016 to 2026, much faster than the average for all occupations, resulting in about 50,400 new jobs. Although this small group includes only four detailed occupations, 3 of the 4 are among the top 30 fastest growing occupations to 2026.

Again, you must remember that these are just projections. This is still pretty exciting stuff right? With this in mind, let’s take a look at some careers that one might pursue if they decide to specialize in the study of data science.

Machine Learning Engineer
Virtually every technological development that has occurred in the last few decades has required to persistent work of machine learning engineers. This is because the world is increasingly leaning on artificial intelligence (AI) and other high-tech creations.

Think about the last time you took a vacation somewhere. You knew the address of where you were going, but you probably didn’t know exactly how to get there. You had likely never been there before, but you weren’t worried that you wouldn’t make it. In fact, you had an exact turn-by-turn roadmap for where you needed to go. Also, you had access to the quickest route to get there. How was all of this possible? Because a lot of data science engineers got together and created the various mapping tools that we all use on our smartphones.

Machine learning engineers help bridge the gap between the raw collection of data and the implementation of that data into various technology products. When they meld these two things together, they end up creating new products that we all use. Thus, their work is both highly valuable and underappreciated. However, the average machine learning engineer will tell you that they don’t do this work for attention. Rather, they believe there is beauty in simply creating something that everyone uses.

Data Architect
Are you the kind of person who can take a big idea and boil it down to its most important components? If that sounds like you, then you may be the perfect person to fill a data architect role. Data architects:

Visualize data frameworks – Not everyone in this world can look at data and see the bigger picture. However, those who can take a large chunk of information and create a framework out of it are highly valuable to organizations. Their mind works differently from most, making them highly sought after.
Define data flows – Data architects draw a specific roadmap of where data is current and which departments generate it. They see how different segments of an organization use and produce data, and they can reorder the structure of that data flow as necessary until only the proper departments receive the data that they require. In other words, they can reorient the way that the company does business so that data gets where it needs to go efficiently.
Turn business needs into technology solutions – Business leaders define the needs that they have, and data architects work with that vision as well as the data that is available to them in order to produce something that the business leaders are proud of. The two work hand-in-hand for data science to get from the concept stage to the point where the business need is fulfilled.
This exciting field is one that many people are attracted to because they know that they at least have a shot at creating something that will be noticed, appreciated, and perhaps turned into a lasting idea that truly flourishes.

Business Intelligence (BI) Developer
In most companies, the data is all around them. However, that doesn’t mean that they necessarily know how to put it to good use. The company may need to hire a business intelligence (BI) developer to assist them in this project.

The primary objective for a BI developer is to create systems where data can be aggregated and reported in a digestible form. Business leaders like to look at charts, graphs, and other visual aids that present their data well. Anything less than that won’t work nearly as well. Business leaders have grown accustomed to seeing the data they require in a certain format. The business intelligence developer can provide that to them.

In addition to this vital service, BI developers also help by:

Developing standards and procedures for data retrieval and use
Works on keeping data systems working at optimal levels
Clears out any duplicate or irrelevant data from the system
Works with the IT security team to keep data secure
Provides assistance with any other duties as assigned
The people who perform this job are called upon to do a lot, but the work can be extremely rewarding. It is yet another way that data science can be used for the betterment of our society.