The position of data scientist is one of the most lucrative jobs in the field of data analytics. It’s even dubbed by the Harvard Business Review as the sexiest job of the 21st century. Glassdoor also termed it as the best job of the year for 2016. So how does the most coveted title in analytics pay? Here’s a 2018 salary guide for Big Data and Data Science.
In 2012, Harvard Business Review titled data scientist as the sexiest job of the 21st century.
The position was no longer limited to data for research purposes. There was already an actual application of data for commercial endeavors. One of the critical applications of data was predicting customer behavior, which is vastly infinite.
Data scientists were insufficient. Thus, they were highly in demand. Which is probably why they got the “sexiest job” title in the market.
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Sexiest Job of the 21st Century
Data scientists are a new breed of high-ranking IT professionals with training and experience in Big Data and Data Science. Theirs is that of a recurring curiosity to explore and discover the big world of information.
The title “data scientist” has only been around for a couple of years. It was coined in 2008 by two respected leads in the field of data and analytics who then worked for Facebook and LinkedIn.
While the title is still young, there are already thousands of people working as data scientists. Both in tech startups and well-established industries. Their sudden emergence into the business scene is a mere reflection for the crucial role of information. Today companies are wrestling with huge quantities of data. The magnitude is that such volumes and varieties of information are those that these businesses have never encountered before.
To tame a wild beast as Big Data, these experts use technologies related to open source tools, data visualization and cloud computing. While the technological breakthroughs help, getting the right people with the right skillset is crucial to putting the innovations to good use.
The demand for data scientist is high.
So high that the demand raced way ahead of supply. The resulting shortage poses as a serious constraint in some industry sectors. With so much data at hand, companies have acknowledged the absolute need for people who will manage it. Then process it to find insights therein.
Currently there are no university programs that formally offer degrees related to Big Data and Data Science.
In addition, there is little consensus on where the role of data scientists fits in a typical organization. Certain industries have yet to determine who these professionals are and what value they can bring to the business.
The first step in filling the void is to truly understand what data scientists can do in companies. It is important to learn what critical skills they possess. And with those skills, it is important to know what fields are those skills needed.
Data Scientists Swim in Big Data and Data Science
So what do data scientists do? Think of Big Data and Data Science as one big ocean. What data scientists do is swim in it. They explore the vast world that is the digital realm. And they make discoveries as they navigate through it.
The world of Big Data and Data Science consists of large quantities of formless, unstructured data. It is the duty of data scientists to organize the sea of vast information to make analysis possible.
In a competitive business landscape where data keep on flowing, challenges exist in identifying reliable information and processing the incomplete ones to come up with a clean resulting set.
Which is why companies need people who are inherently curious. Intensely curious to learn new things on a given set of information. A person who willingly goes beneath the surface and dig deep. Someone who finds questions. Then purify it into a clear set of hypothesis for testing.
With the vast information flowing, today’s businesses need this type of associative thinking. Which is why data scientists are crucial members of an organization.
Is Big Data and Data Science Still Sexy?
Yes, it is today. And yes, it will still be five or ten years from today. And data scientists and its related careers are and will still be sexy as ever. These professionals will be demand.
However, the downside to this increasing demand for data scientists is that many people will come forward, claiming skills in Big Data and Data Science.
So what does a qualified data scientist bring to the table?
As the volume and variety of data continues to grow, the need for data scientists will remain. They find the needle in the haystacks of data. With data discoveries, these professionals contribute to:
Product research and development,
Discovering breakthroughs,
Attracting and retaining customers, and
Managing risks.
Big Data and Data Science puts companies in the right place, at the right time, with the right offerings, for the right customers. And this is where data scientists can help.
How Much Do Data Scientists and Related Professionals Earn?
The higher the demand, the more lucrative the amount of pay.
Thus, the role of data scientist commands one of the best pays in the job market. According to the website indeed.com, the U.S. average salary for the title is about $117,000. The rate is higher for data scientists who have over five years of experience.
As mentioned, there are related careers in Big Data and Data Science. It isn’t just data scientists. Wondering what are they?
Big Data Engineers
Big Data engineers create and manage the infrastructure required to handle Big Data. Thus, they need to have the technical skills to distill vast amounts of information accurately.
Data scientists and Big Data engineers work closely. In fact, both their job descriptions are virtually alike. The stark distinction, however, is that Big Data engineers focus on the engineering side of things. They are not dependent on machine learning or statistics.
According to indeed.com, Big Data engineers in the U.S. receive an average of $147,000 a year.
Machine Learning Experts
Machine learning is about teaching computers to emulate action. This process heavily depends on the way the algorithm is designed, which allows computers to learn how to learn. This is a field handled by machine learning experts.
Typically there is not predefined set of instructions in machine learning. What the experts do is put in an algorithm that helps computers predict and perform tasks based on certain patterns.
As a niche sector in IT development, machine learning experts receive a relatively higher salary rate. As reported by indeed.com, these professionals get an average of about $112,000 a year.
Business Analysts
Organizations that encounter a vast volume and variety of information require business analysts. These professionals handle the assessment of the business and technology model of an industry.
Business analysts process the incoming data and filter the usable information. As the demand for this position is on the rise, these professionals earn an average of $89,000 per year.
Information Manager
Dispersal of vital information heavily relies on the proper acquisition and management of data. To this end, deciding whether to keep or ignore a certain information is a critical process. This is a job that information managers do.
Across the U.S., information managers receive an average annual salary of about $97,000.
Business Intelligence Experts
Business intelligence covers an extensive range of activities. In a nutshell, this particular niche includes deployment of various applications and software that will help companies decipher critical information from raw data.
Other activities involved in business intelligence include data mining and analytical processing. Basically any process that churns out any data and turn it into actionable insights is business intelligence.
Serving a crucial need, business intelligence experts in the U.S. get an average of about $102,000 a year.
Here’s How Much Big Companies are Paying
At about $117,000 per year, that’s the average base pay for data scientists. However, the salary range is between $89,000 and $242,000.
In addition to the basic rate, data scientists also receive an average annual bonus of about $24,000. There’s also a signing bonus, which amounts to about $15,000. And on top of that, an annual equity of about $53,000.
The ride-sharing app Lyft pays the highest base salary for data scientists at an average of about $167,000. Facebook and Amazon follows at $159,000 and $151,000, respectively. Apple pays about $150,000 while Airbnb shells out about $117,000.
Social networking websites Twitter and LinkedIn gives out about $135,000 and $139,000, respectively, to their data scientists. Microsoft and IBM data scientists earn about $119,000 and $111,000, respectively.