When it comes to making a career choice, there are many different career paths to choose from. This, beyond doubt, is one of the most critical life decisions you will ever make, and hence you should consider many factors before deciding the career path for yourself. While exploring various career options that are popular today, you may notice data science for a number of reasons, but often because of its high overall compensation and salary.
Data scientists are paid so much because there is a large global demand for their skills, their work is extremely valuable to most companies, the supply of these professionals is scarce, they need several advanced skills that take years to master, and finally because their work can be extremely stressful at times.
In this article, we will first explore answers to some basic questions, such as – What a data scientist is? What do they do for a living? Why are they in such high demand right now? Etc. Then, we will gradually deep dive into some of the main reasons due to which this profession currently offers such high salaries. Finally, we will delve into discussing some factors that you should consider when deciding whether data science is the right career choice for you. Therefore, if you are someone who is considering data science as a career or are someone who is simply trying to understand the reasons behind high salaries in the data science profession, I am confident that you will find this article very interesting.
Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!
Table of Contents
What Is a Data Scientist?
Before we take a look at why data scientists are paid so much, we need to first explore what this profession is like and the work these professionals do on a daily basis. This is an exciting job that has endless possibilities in the world of data and computer science. There are also many possibilities in the future that promise to challenge and entertain those who decide to take on this profession today.
To start, a data scientist will be a professional who spends his/her day collecting, analyzing, and then interpreting large amounts of data. In fact, these datasets are often so large that the data scientist can’t possibly dream of doing it all manually. Millions or more data points in each set are not uncommon.
Instead of trying to do all of this manually, a data scientist will choose to work with various algorithms and other tools to make it easier to see patterns and other important information within the data.
The Role of a Data Scientist
The role of a data scientist will need you to wear multiple hats and be an expert in multiple domains at the same time. For example, a data scientist will often need to be a computer science professional, statistician, a researcher, a business guru, and a mathematician – all in one. Additionally, these professionals will need to have a good idea of using machine learning and other similar techniques at the same time.
How They Use the Data?
Data scientists need to be comfortable with analyzing large amounts of data in order to see what is hidden inside. They need to take these large datasets in order to make educated hypotheses and analyze trends in the market and about the customer. This is why many companies will hire a data scientist so that these professionals can empower them to make important business decisions that are informed by data.
For example, a business may spend time gathering large amounts of data on their customers. This can include purchases, surveys, social media interactions, and other sources, depending on the type of business. They will then pile this data into one location and hope to somehow make sense of it all.
This is where data scientists come in. Using different forms of analysis and data wrangling techniques, they will create algorithms that help sort out the data, and thereby show trends in data and the likely outcomes depending on different scenarios that the company can go with. When done well, the work of the data scientist will help companies make smart predictions that put them ahead of the competition.
Why Are Data Scientists in High Demand?
There are many reasons why a data scientist’s job is in high demand today. These individuals can help businesses and government entities in many ways. With the use of data and information, these professionals provide their employers with necessary analysis and assessment so that these companies can stay ahead of the competition. Some of the reasons that data scientists are in such high demand include:
There Is So Much Data
It is amazing how much data is found all around us all the time. Today, most businesses have moved at least a part of their operation online, and with this transition the amount of data that is available to them for analysis has exploded. Plus, businesses today are more than willing to use this collected data to better understand customer needs, optimize their operations and come up with more targeted ways to capture the market share while delighting their customers.
In fact, there are more than 6 billion connected devices throughout the world, with new data in the millions of terabytes being generated every day. There is a ton of information waiting to be explored and understood, and a data scientist has all the experience and expertise to get this done.
Data Is More Affordable
Historically, it used to cost businesses a lot of money to gather any useful data. There weren’t any online platforms to work with in the past, and the company would need to spend a lot of time, money, and resources on figuring out how to collect the data. Thanks to our modern world and all the technology present, companies today are able to gather large amounts of data for a relatively low cost.
There Are More Ways to Use Data Science
The more applications of data science available, the more professionals you need to work on solving those problems. Every industry out there will generate or rely on all that data available. For example, healthcare will use data to provide better treatments; agriculture will use it to figure out how to control the cycles of water and come up with better crop yields, and more. Every industry needs a data scientist to help them figure out the trends in the data and use those insights wisely.
A data scientist can help to sort through all of the data and make it organized. Because there is so much data to sort through, it is difficult to work on this without a dedicated data science professional.
It Gives Companies a Competitive Edge
Just because it is simple to gather a lot of data doesn’t mean that it is easy to sort through it and understand what that data is saying. Once a company can gain this insight and utilize the data well, it can gain a huge competitive edge over its competitors.
It is amazing how much information can be found in all that data. But due to the fact that the data is so vast and large, with so many different parts to it, many companies can miss out on important information that could have put them ahead of the competition. Once the data scientist comes into the game, they can sort through all the noise and come up with data-driven solutions that work for the company.
Why Are Data Scientists Paid So Much?
There is a good mixture of reasons why data scientists can earn such high incomes. Between a high demand for this position all throughout the world, a low supply of qualified individuals who can do the job, and more, it is no wonder that many data scientists are able to start their career with a good salary. Some of the reasons that a data scientist is paid so much include:
There Is Global Demand for Them
It isn’t just companies in America who need to work with data scientists. Companies all throughout the world can hugely benefit from these professionals, from medium-sized companies to those that are much larger. This global demand allows for plenty of job opportunities for the right candidate and can open up more income choices as well.
Since the supply of qualified data scientists is fairly low, the demand being a worldwide factor makes the income levels even higher. Data scientists not only have their choice of the type of work they want to do, but also where they want to live in the world too.
Their Work Is Valuable
The work that a data scientist performs is extremely valuable to their employers. It may seem like they just mess around with numbers each day, but the work they do with these numbers is really valuable. Since new data comes in at an alarming pace, with things changing each week, and sometimes each day, a data scientist who can keep up with all of this is a valuable commodity for most companies.
There is a lot of neat work that a data scientist will do for their employer, and all of this takes them time and talent. A good company will be more than willing to pay a high salary for all this work. Some of the tasks for which data scientist works hard, thereby generating immense value to their employers include:
- They can gather data. A data scientist may come in on the ground floor and help set up channels for the company to start gathering the right data. This way, the company has a steady stream of valuable data on their products, their business, and their customers.
- They can sort the data. Since there is such a large amount of data coming in, a data scientist has to be adept at sorting the data into stuff that is valuable and stuff that is a waste of time. Some of the data is important, and other data is just a lot of noise.
- Analyze the data. While sorting through the data, the data scientist must analyze what the data says. They may use a variety of algorithms to help make this quick and effective.
- Work with algorithms. These are basically mathematical equations applied to the data set through computer programming and help sort out all the data. The data scientist must have a general idea of what the data contains and what they are looking for. But the algorithm can make it easier to sort through the data and see some easy trends and patterns in no time.
- Present the results. Once the data scientist has had the time to analyze and work with the data, they need to present it to those who matter in the company. It needs to be presented in a way that helps the business owner and other important decision-makers understand what is going on and are empowered to make the best possible decision based on insights extracted from data.
There Are Not a Lot of Professionals Trained for the Job
We already discussed how much global demand there is for data scientists. Companies throughout the world, many of them large, need data scientists to ensure they make educated decisions about their work. Whether it includes understanding what products to design, how to reach the customer, or to handle marketing, data scientists are valuable for many companies.
However, there is a lack of supply for these professionals. The requirements to handle this job are hard. Alongside handling a large amount of data, to be successful as a data science professional, you need to develop many other skills and have a good understanding of computer sciences and programming languages. Even with the high pay that many companies are willing to pay, this is a challenging career, and not many choose to go after it.
Out of the few who complete the required education and land a job, the pay is high to entice them to stick around. Many companies will offer attractive salaries along with other benefits to hire a good data scientist, or even to take one away from another company.
Need Advanced Skills
It is important to note that there is a high level of skill necessary to become a data scientist. In fact, this demand is one of the biggest reasons that the supply of professionals for this job is so low. It takes a lot of time and effort to gain these skills, and many people have no desire to do that.
For example, to be a data scientist, you need to be really good at several advanced skills, including statistics, programming, and math. Learning how to excel in just one of these at a time is challenging enough, much less trying to handle it with all three at the same time. Failure to do well in these subjects will make it impossible to do well in this role.
Savvy on Big Data
Of course, a data scientist needs to know quite a bit about big data. It has only been in the past few years that almost 90% of the information in the world was created. That is quite a lot of information for a relatively short amount of time. While data may have been limited in the past and easy for one or two people to sort through, that is simply impossible today.
A data scientist has to find ways to get through all that data, as accurately as possible, and learn what is inside of it. They can then use that information to help businesses make more informed decisions. They can’t do this manually, so they have to understand big data and how all this works.
Knowing the Industry
In addition to having a good grasp on the STEM skills above, the data scientist needs to understand how the data will be used and how to analyze it towards market trends. This means they need to really know the industry they plan to work with. You may do great with sorting out data and analyzing it. But if you can’t use that data to make good deductions based on the industry, then your work is worthless to the company.
There are many different industries that will work with data, but they all need to use it differently. Retail businesses may choose to use it to decide where to place their products and the type of advertising to use. Insurance companies may use it to determine risk. Banking can use it to keep clients’ information and money safe.
The data scientist has to understand this and learn how to not only handle the data but also how to actually leverage that data in the industry that they plan to work in. Combining this all together with the high skills can make it tough to find professionals that fit all the requirements of these data science jobs. Hence, this talent is greatly valued at most companies, and as a result, these resources are paid very handsomely.
Needs an Advanced Degree
While there are a few data scientists who are able to gain experience in the field and get a good job without a degree, this is not as common. It is hard to gain this kind of experience without some time in college, but it is possible with a little bit of work and ingenuity.
Most data scientists will start with a Bachelor’s degree. Several good major choices for undergraduate majors include physics, math, computer science, or IT depending on your degree. Many aspiring data scientists will go on to also earn a master’s degree to help them gain more of a competitive edge in the market, though it is not necessary.
There are a few choices to pick from when gaining your master’s degree. To make the degree go a little farther, you should consider doing something in data or another related field. IT and computer science are good places to start as well. In some cases, you may be able to get a job in data science or computer science and learn from there or get your education paid for.
Data Means Money for Many Companies
One reason that a data scientist gets such a high salary is that they are worth that much to their employers. It is easy for companies to gather large amounts of data. They can do this in no time. The trouble comes when it is time to take this data and make sense out of it. Companies understand that properly understanding this data and utilizing it well can make them very profitable in the future.
The problem is that many CEOs and business leaders have no idea how to sort through and analyze the data themselves. But they are willing to pay a data scientist to help them with this. If the data scientist can provide them with insights out of that data to make informed decisions and to really reach their customers, then the data scientist is worth every penny the company spends.
Goes Against a Traditional Approach
In the past, many businesses would spend their time gathering a little bit of data and then using their intuition to make these decisions. Naturally, those with good intuition and who have done the industry for a long time would be better at this job. Plus, historically, at most companies there wasn’t a lot of data available, so many times this intuition and good business sense were the only way to make informed decisions.
Thanks to the cutting edge data analysis techniques and the large amounts of data available, companies no longer need to rely so much on their intuition. This also helps take some of the risks out of their decisions. The data, when sorted well by the data scientist, will have turned into hard evidence to use towards any decision the company needs to make.
However, even though basing decisions on data has proven very successful over the years, there are many companies that just are not comfortable with it. Even if they hire a data scientist, this professional may have to spend time proving themselves and their data before it is even considered, and this can be stressful to work with.
The Work Is Hard
It is easy to assume that working as a data scientist is really easy. Many people fall under the assumption that the data scientist needs to plug in a few algorithms or equations into a computer, and all the work is done for them. There is quite a bit more to the process than that, and understanding how this works can make a world of difference in seeing why a data scientist earns a high salary.
The data scientist has to hold many roles. They need to know how to work with computers, how to handle math and science, and how to sort through a lot of data. They also need to have a good understanding of how to work with machine learning, which is a complex field all on its own.
Plus, the data they work with is always updating and changing. This is not a static job that is done once and then all is good. Instead, it is a job that the data scientist has to keep up with all the time. Even after coming up with advice and patterns on the data, the data scientist will need to check and double-check their work to make sure it is accurate and the best information for their employer.
Is It Worth It to Become a Data Scientist?
Before you choose to become a data scientist, you need to determine whether it is worth it to become a data scientist. There is a growing number of people who choose this as their career choice because it is an attractive option and comes with a lot of pay, and there are many great career opportunities to work with as well.
But the work can sometimes be challenging, and with so much talent jumping into the field, it does pose some challenges.
The Salary of a Data Scientist
The salary is often one of the most appealing parts of this job and one of the reasons so many people flock to getting certified and ready to take on this role. It is estimated that the average salary for a data scientist is around $113,000 a year, with some making even more than that amount. This is an attractive enough amount to get others to jump in and give this career domain a chance.
Lots of Career Options
Since many businesses need to utilize all that data out there, there are many great job opportunities available for a data scientist. This makes it an exciting career to choose. You can pick what industry to focus on, and even which part of data science you want to focus on. This can make working more exciting than other types of jobs.
Different Types of Certificates
A data scientist also has some different choices in the certificates they would like to use. There are some basic certificates that will get you started and may provide more experience in a short amount of time. There is also the option to get an associate’s degree or a bachelor’s degree in the field to gain more comprehensive knowledge and stand out from the competition.
The Problem
Data scientists often need to work long hours for the work that needs to be accomplished. They have to deal with data all day long to make their clients or employers happy, and they need to be incredibly accurate the whole time as well. And because there is a higher appeal with this position, there is a lot of competition, which makes it harder for new, aspiring data scientists to get into the game.
There are a lot of benefits that come with being a data scientist, but there are also a few drawbacks that need to be seen as well. This is not a career you can get into just because of the money; it has to be something you are passionate about and ready to fight the competition off for.
Author’s Recommendations: Top Data Science Resources To Consider
Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.
- DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
- IBM Data Science Professional Certificate: If you are looking for a data science credential that has strong industry recognition but does not involve too heavy of an effort: Click Here To Enroll Into The IBM Data Science Professional Certificate Program Today! (To learn more: Check out my full review of this certificate program here)
- MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
- Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.
Conclusion
The field of data science has grown like crazy over the past few years. Many companies are finding the value of gathering and analyzing data, and they need a data scientist to go through the data and make sense out of it. With so much growth potential and many opportunities for exciting work, it is no wonder that data science, as a career, is doing so well.
BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.
Affiliate Disclosure: We participate in several affiliate programs and may be compensated if you make a purchase using our referral link, at no additional cost to you. You can, however, trust the integrity of our recommendation. Affiliate programs exist even for products that we are not recommending. We only choose to recommend you the products that we actually believe in.
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