Data science — it’s the hidden magic behind nearly all of your tech-related ventures. If you’re on social media, it’s the algorithms that decide which posts and comments end up on your feed. If you’re lost and relying on Google Maps, it’s the GPS that’s busy mapping out your immediate surroundings and pinning down your location. Data science is a broad field of technology that encompasses multiple disciplines and industries.
So it’s no wonder that this field of study is quickly becoming one of the most in-demand in the market, with multinational corporations and small businesses worldwide on the hunt for data scientists they can call their own. Better yet, it’s a high-paying career with plenty of opportunity for growth.
If you’re trying to decide which college major to choose and have always had an affinity for mathematics, science, and technology, then this may be the field for you!
Why Does Data Science Matter?
Now that everybody interacts with technology to some degree, data scientists are in hot demand because they can help businesses plan better. Here are some quick examples of some of the behind-the-scenes work that relies on data science:
- On the internet, data science refines the answers you get for every internet search based on your previous searches. It also makes the ads you view while scrolling through social media more accurate to your interests.
- For avid gamers, data science helps create a more personalized experience. Enemies can become harder to defeat or “learn” from your play style as you level up. In augmented reality games like Pokemon Go, the game uses GPS data to “place” the Pokemon that are available to catch in real-life locations. This makes your quest to “catch ’em all” more realistic by putting sand-type Pokemon in deserts or beaches, water-type Pokemon on rainy days, and grass-type Pokemon in forests!
- Data science is the magic behind the study apps you’ve been using to ace your classes.
- The airline industry uses data science to predict flight delays, route airplanes, and drive customer loyalty programs.
Data science is essential in all situations where technology and data exist. Scientists in this field are crucial for maximizing an organization’s time, resources, and labor.
What Does a Data Scientist Do?
Data scientists can be found in any industry, collaborating with other professionals to build algorithms that can organize and extract massive troves of information. This information is used to help the company analyze its past movements, develop strategies, and plan for the future.
In addition, data scientists collaborate with various stakeholders across an organization or business to advise on the best course of action based on their data. They’re responsible for translating the complex tech jargon of machine learning, big data, and mathematical modeling into layman’s terms for non-tech professionals.
Data Science Salaries
The work of a data scientist is indeed complex and challenging. Fortunately, the payoff for this unique skill set is reflected in the compensation. According to Glassdoor, data scientists have the second highest-paying job in America, with a median base salary of $113,736 per year.
Other related jobs that made the list are enterprise architects ($131,361), machine learning engineers ($104,837), and data analysts ($70,000).
Data Science Career Outlook
Careers in data science are not just lucrative — they’re on the rise, too! According to the US Bureau of Labor Statistics, the job outlook for data scientists and other computer and information research is projected to increase by 15 percent between 2019 and 2029. This employment growth rate is much faster than average for all occupations, which is only an average of four percent. It’s a great time to become a data scientist!
Education for a Career in Data Science
Data science is a blanket term for many tech concepts such as machine learning, artificial intelligence, and big data. As a result, you can choose from various educational paths and specializations to excel in this industry.
Data Science Degree Requirements
To proceed with a career as a data scientist, you’ll likely need a bachelor’s degree in a field such as information technology, computer science, math, or physics.
The most lucrative career prospects within the industry will require a master’s degree, so after you graduate and rack up some work experience, you can consider a graduate degree to upgrade your pay. Don’t be intimidated by the long haul — most data scientists start out small and eventually build their way up, just like any other occupation!
It’s no surprise that you need to be a bit of a tech geek before you enter the industry. If you’re thinking about applying to colleges, make sure you build an application that showcases your passion and expertise for mathematics, science, and technology.
There is no hard and fast rule as to who can become a data scientist. The main prerequisite for any undergraduate degree program will be a demonstrated interest in the subject, preferably backed up by good high school grades in STEM-related classes. As long as you are passionate about these topics, you’re likely to have a fighting chance!
Best Data Science Colleges in the US
Most universities have started offering degrees specifically for data science to capitalize on the rise in demand for professionals within the field. According to US News, the University of California, Berkeley is the best college in the country for studying data science, followed by the Massachusetts Institute of Technology (MIT) and Carnegie Mellon University.
If you are a budding data scientist, try looking for colleges that connect you to industry professionals and help you network while you study. For example, MIT has an Analytics Capstone Project, allowing you to work on data science problems with businesses. Any program that offers real-world experience and connections will help set you up for your future career.
Skills Needed for a Career in Data Science
Since data scientists go back and forth between machines and other professionals to extrapolate data, they often need to have plenty of soft skills to complement their tech knowledge. Here are some of the valuable useful skills data scientists need to be more competitive in the job market.
Regardless of whether you’re working in a multinational corporation or a startup, it’s crucial to know how to get your message across to your colleagues so that they can make the most out of the information you’ve extracted. You’ll find yourself in plenty of situations where you need to deal with a diverse group of people in a team.
You’ll be working in a team, managing deadlines, and coordinating with various departments in your line of work. To make the entire process more efficient, data science professionals need to know how to manage project timelines, build relationships, take command, and distribute work evenly.
In mathematical modeling, you learn how to create formulas to describe how a system works. Models are a great way to make your work easier because they allow you to evaluate different scenarios and outcomes quickly. You’ll need to be able to cross-reference the information you have with the mathematical models to calculate and predict information from the data.
One aspect of data science is building algorithms or creating models that can help businesses automate information management. This means that you will need to be familiar with some basic programming to execute a successful data science project. Look into common programming languages, such as Python or Java, which are popular choices because they’re in-demand and (relatively) easy to pick up.
Since you’ll be working with data, you need to be familiar with how it is stored, organized, and managed. Having a solid foundation in database management systems (DBMS) will work to your advantage when accessing and interpreting data.
One big part of a data scientist’s job is to refine machines to process information better and learn from the data. You’ll be working with artificial intelligence to help systems identify patterns and make decisions with little to no human intervention.
To make the most out of your technical skills, you’ll need to understand how they can benefit a business. For example, you may need to know how an organization is structured to understand who to approach for collaboration. You may also need to decide for yourself how the data you’ve gathered is relevant to the organization.
Are You the Next Future Data Scientist?
Data scientists are often curious, driven, and results-oriented. They’re passionate about mathematics, with a strong background in statistics, linear algebra, and programming. If you think you have what it takes to join the field, this is your sign to pursue your dreams!
Start writing up your college applications and sending them to universities that can support your goal of becoming a data scientist. In a world where everyone relies on technology for almost everything, it’s one of the most stable and lucrative careers you can go for.
Frequently Asked Questions About Data Science
What are some examples of data science jobs?
Data science jobs include data scientist, data analyst, and statistician. However, you can also go for plenty of other adjacent positions, like a machine learning engineer or scientist, especially if you’re into software engineering, algorithms, and deep learning techniques.
You could even specialize in data architecture to improve the work of business and applications. These professionals eventually can become enterprise architects, applications architects, and infrastructure architects.
How much money can I make as a data scientist?
You could definitely earn enough to live a comfortable life if you decide to pursue a place in the industry. While the numbers differ from one source to another (Indeed reports it to be $120,099 per year, while Glassdoor states that it is $113,736), most data scientists earn above $100,000 yearly in the United States.
Is it hard to get a job in data science?
Data science professionals are in demand all around the world! It can be a highly lucrative profession, and the scarcity of talent in this field means that businesses are constantly looking for a data scientist they can trust to work for their organization. However, to maximize their earnings and give themselves a competitive edge, many professionals pursue an advanced degree.