What Does a Data Scientist Do?
As a data scientist, you will spend your time working with data. Sometimes, the data is already collected for you. Other times, however, you may have to develop programs that collect the data. Your responsibility is to collect, store, and analyze the data to solve analytically-complex problems. Sometimes, though, your main goal may be to make meaningful use out of the data, with no complex problem to solve. Regardless of your responsibilities as a data scientist, you are going to be working with various software tools and you are going to need an extensive amount of knowledge related to programming, coding, mining, and query languages.
How Much Does a Data Scientist Make Each Year?
As Big Data continues to increase in its value, there will continue to be an even greater need for data scientists. These types of scientists are the gurus with the magic to make meaningful sense out of the Big Data being collected. By analyzing this data, they are able to provide employers with recommendations that power smart business decisions. Big Data just became popular over the past ten years, so there hasn’t been much time for people to become data scientists. Now, however, more employers than ever are looking to employ data scientists and they are willing to pay a pretty penny for their salaries.
According to the University of Wisconsin, the average salary for a data scientist is upward of $113,000 a year. Starting out in this field of work, you probably won’t make that much, but still yet, starting-level salaries tend to be anywhere from $50,000 to $95,000 a year.
Why Does a Data Scientist Make So Much Money?
According to Indeed.com, “data scientists salaries are 113 percent more than [other] average salaries.” Why do data scientists get paid so well for their responsibilities? First and foremost, these scientists make such good money because their skills are able to propel a business toward smarter decision making; these smarter decisions can save money and lead to an increase in profit levels.
There is much that goes into being a data scientist. It’s not all about mathematics and computer programming. It’s about mastering statistics and using one’s intuition to derive insights that he or she knows will be of benefit to the employer. Without this intuition, a data scientist is rarely successful, and since not that many people have been able to master this intuition and combine it with analytical thinking, distinguished data scientists are quite hard to come by; thus being another reason they are paid so well.
One of the best ways to understand why data scientists make so much money is by taking a look at Mitchell Sanders words, “a good data scientist blends domain knowledge (i.e., they know the banking or retail or whatever industry they operate in), math and statistics expertise, and programming skills. Too many organizations think that they just need one of these areas covered. In fact, far too many overlook the people already within their own organizations: those that have the domain knowledge necessary to asking intelligent questions of their data.”
Svetlana Sicular, an analyst with Garner, states that because existing employees already have such a vast range of domain knowledge, it is always important for employers to look within for data scientists before bringing in someone who knows little about the company and the industry it operates in.
Are There Ways to Improve Your Salary As a Data Scientist?
Regardless of how long you have been working in the field of data science, there are factors that can influence how much money you make. For starters, your years of experience in this line of work will largely impact the amount employers are willing to pay you. More so, your ability to solve complex problems using domain knowledge combined with statistics and coding will impact how much money you are able to make.
If you are wanting to optimize your salary as a data scientist, you will need to become familiar with as many data science tools as possible. Here’s a look at the tools that can bring you the most benefit in regards to raising your salary.
According to the O’Reilly’s Data Science Survey, being able to work with the Apache Spark tool can greatly increase your salary. Another language tool that you should be familiar with working with is Scala. Learning how to operate both of these tools can increase your salary by as much as $15,000 a year; that’s an extra $1,250 a month. D3 is another tool that can improve your salary, with an $8,000 positive boost. More so, being extremely familiar with cloud computing can boost your salary. Those who know how to use Amazon Elastic Mapreduce are typically able to increase their salary by $6,000.
It is also worth pointing out that data scientists who know how to use at least 15 tools are generally able to make $30,000 more than those who are only familiar with 10 to 14 tools. As you can see, the more tools you know how to use, the higher salary will likely be.
Another factor that is going to affect your salary as a data scientist is the industry you work in. Different industries face different types of data challenges, and some of these challenges are more difficult than others. In industries where there are extremely complex challenges to overcome, data scientists are usually paid more generously for their services. The top-paying industries are:
- Search/social networking
- Manufacturing(non IT)
You should also know that some companies are well-known for paying their data scientists top dollar. As of 2018, Amazon is the top-paying company for data scientists, followed then by Google and Facebook.
Even if you can’t secure a job through one of these top-paying companies, there is no need to fret. Many startups are more than willing to adequately compensate data scientists for their services. While there aren’t many hardware startups that start their data scientists out at making upward of $100,000 a year, there are many enterprise software startups that do. As you can see, it’s all about the industry you are willing to work in.
Moving on, location is another factor that impacts your salary in this line of work. And fortunately, the United States boasts the highest average salary for data scientists. If you are looking for a position that comes with an extremely high salary, you are going to find certain locations pay better than others. For example, San Jose and San Francisco are the two top spots to work, while Los Angeles and Austin fall well below the national average salary.
Which Schools Offer Data Science Degree Programs?
There are many schools in the United States that offer data science programs. Some employers, however, will prefer experience and knowledge over a credential. If you have a specific employer you want to gain employment through, it is recommended to pinpoint the employer’s preferences. You may find that all of those free data science MOOCs and boot camps you are completed online are sufficient to gain employment. If you want to earn a degree, though, make sure to check out the schools listed below:
- The University of Arkansas at Little Rock – Masters and Doctoral Programs
- Arizona State University – Certificate and Masters Program
- California Polytechnic State University – Bachelor’s and Master’s Programs
- Chapman University – Masters and Doctoral Programs
- Georgetown University – Masters Programs
Do You Need a Masters Degree to Be a Data Scientist?
According to KDnuggets.com, you don’t necessarily have to have a masters degree to become a data scientist, but some experts argue with this belief. Steven Miller, a data maestro at IBM, says, “To learn data science — absolutely [you need a masters degree]. A few schools are building undergraduate programs that will be akin to a computer science degree. You will learn core skills, but they won’t make you a scientist who will be advancing the field.” A developer at Restaurant Technologies, Sal DiStefano, however, says, “Remember that Data Scientist is just a Title. (A media hyped title) Some give themselves or have this title because that’s the work they do, not because they have a particular degree. Some may hold degrees in Statistics, Mathematics, Computer Science, the disciplines vary.”
Once you gain employment as a data scientist, you are likely going to make close to $100,000 a year. You may start out at a lower salary during your first five years, but experience will boost your salary significantly fairly quickly. Also important to keep in mind is that the location of your job, as well as the size of your employer, will influence your salary. If you are willing to relocate to an area, such as San Jose, you can make really good money.