A data scientist is a normal analyst or scientist who applies statistical and mathematical
modeling on a bunch of raw data to extract relevant information from it. With the rising
competition in each field of business, and more companies entering the fray every day, all the major businesses have leaned towards data analytics for enhancing their output.
This rising trend has led to an exponential increase in career opportunities for data scientists. The results obtained from data analysis is vital and is used for important decisions by the company, so the position of a data scientist carries a heavy responsibility because a wrong analysis of the collected data can cause a loss worth millions for the company.
This is paradoxical as a data scientist was hired to save millions worth of money for the company. Thus, the importance of the position of a data scientist has caused the salaries to skyrocket to exorbitant amounts. The average salary of an established data scientist is nearly equal to $115,436 and even the entry-level jobs borrow from an average range of salaries from $50,000 to $95,000. All this data and figures are taken from ‘Glass door’.(www.glassdoor.in)
Since this data analytics industry is seeing boom time right now, the amount of competition to land a decent job as a data scientist is fierce and hard. The companies are being extremely cautious about selecting data scientists because it is a very important business decision for the entire company. Although we see that the basic salary level of a data scientist is higher when compared with most of the other jobs in the market, the amount of the salary depends on various factors. The factors affecting the pay scale of a data scientist can be listed as:
Job designation- A data scientist is an ambiguous title and does not refer to any single role in the job. Data analysis is a complex procedure and involves many roles to be played by the members on the team, which includes data collection, data processing, data visualization, predictive forecasting and many more. Some people may even be designated to do a managerial role and not deal with any of the technical aspects, so it becomes important to know the exact designation of the job to determine the salary received by the individual. This works on the ladder principle and the closer the employee gets to the administrative level, such as presenting and communicating business plans obtained from the data analysis, the higher the salary. Some of the common designations obtained as a data scientist job are a data analyst,data manager, data scientist, and data engineer.
Field or Industry- Most of the industries are employing data scientists in almost every arena of trade known, but there are some fields that are more dependent on the data science techniques when compared to others. Some of the industries which are heavily dependent on data science are the banking and finance sectors, cloud service providers, web hosting enterprises, search engine browsers, social networking giants, CDN and many more. Since these companies are more reliant on data analytics than any other industry, the most highly paid data scientists are always found in worldwide technical giant firms like Google, Apple, Microsoft, Twitter, Facebook, Airbnb, etc., with the highest salary figures nearly reaching the value of $155,000. Even the lowest margins of salary in this sector for a data scientist is approximately $120,000.
Amount of experience- The experience is one of the most vital factors of any job. The pay
scale of any job depends heavily on the amount of experience the person has in the field.
According to the experience level, the various diversification of the pay scale can be done as entry-level, mid-level and experienced levels. This is something that is gained by working hard. It’s been seen that as time passes, the salaries of a data scientist keep on increasing. The salary level for the entry-level data scientist is very high, nearly $95,000, and the salaries for the experienced level are going as high as $250,000.
Level of education- Being a data scientist is not an easy job and getting the right combination of subjects is even harder. At the minimum level, every data scientist should know how to write code, but data science is a very vast field and machine learning and AI are but a snapshot of the various subjects and concepts it encompasses. So, having the right education plays a very important role in determining the salary of a data scientist. Some of the skills that a professional data scientist should have include cloud computing, data visualization and optimizing open source tools, and it is not enough to just know how to use them. A data scientist should be highly skilled in these software tools to extract the underlying information and patterns which are necessary for making important business decisions. This means the data scientist should have a very deep understanding of these tools to gain an insight into the subject matter for the benefit of the organization.
Size of the enterprise- The size of the enterprise is a common factor for determining the
salary in any industry and it is easier to understand its impact. It is very easy to understand that the larger the company’s size gets, the higher the salary of a data scientist will be. With the increase in the size of the enterprise, the market size of the concern also increases and therefore the data required to be processed also increases simultaneously. As a company expands its market, it has to focus its business strategies on multiple locations. This multiplies the work and naturally the salary of a data scientist. A company with a larger size will pay more attention to data analysis as compared to a small scale because of the sheer amount of risk involved, so the job of a data scientist again becomes more important for the company and they become willing to pay more for the job in order to attract the most efficient and skilled data scientists available to gain an edge over their competitors.
Regional factors- This is more of a socio-political factor and doesn’t necessarily have any kind of control over it. The more developed countries have comparatively more technical awareness as compared to the lesser developed nations, so the demand and importance of data science are more profound in the developed nations compared to the underdeveloped ones. This leads to a clear demarcation between the regions paying more of a salary for a data scientist job and those offering a lower salary package. The western nations lead the fray with the US paying the highest amount for a data scientist job due to the fact that most of the large-scale IT industries are based there. It also has the highest number of data scientists along with the highest salaries. The south and east Asian regions are at the lower level but are gaining rapidly due to an increase in innovations from these countries. Technical education has now become a priority in the under-developed nations as well and they are producing more and more talented data scientists with each passing day.
All these factors make the job of a data scientist very lucrative and someone might almost be tempted to think that this is the most comfortable career option available, but make no mistake about this, being a data scientist is a very difficult job and excelling in it is even more difficult. The job of a data scientist is very meticulous and they have to constantly operate under a lot of work pressure because if a data scientist fails to provide any constructive results about how to improve the business strategies, then the work of the data scientist is deemed to be a waste.
The high salaries paid by the companies is due to the fact that the skills of a professional and efficient data scientist are extremely exclusive and it takes a lot of hard work and persistence to excel at the job. This makes the job of a data scientist very exclusive and sought-after. The world is becoming more and more digitized every day and it is safe to assume that it will continue for at least 50 more years to come, so the need for data scientists will skyrocket in the future.
The market for data science is growing exponentially right now and taking the correct steps will ensure a bright future. Many large-scale enterprises are providing hefty salaries to data
scientists in exchange for their knowledge. The opportunities and pay scale for the position of a data scientist will keep increasing. However, with all the increasing opportunities, the amount of competition for landing a job will also increase and the skills required to become a data scientist will become more exclusive with each passing day. click here to learn more about data science.
I am Bharani Kumar Depuru, eminent Digital Transformation Specialist with over 15+ years of
professional experience in Emerging Technologies consulting. I am an alumnus of IIT &amp;
ISB and serve on the board of multiple companies in devising their strategies.
Alumnus of ISB and IIT with 15+ years of experience working in various capacities with companies
including HSBC, ITC Infotech, Infosys, Deloitte. Performing consulting for various companies on
Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence,
Big Data Analytics, Industrial IoT, Business Intelligence, Business Management Consulting,
etc., are a few of the prime activities performed. Worked across various lines of business
including IT, Quality Management, Project Management, IT Service Management, etc. Notable
Clients for whom Data Science, Machine Learning and AI implementations are performed
includes: Coca Cola, Tata Trusts, Trujet, Yatra, Korean Airlines, etc.
Director of 360DigiTMG Headquartered in India, 360DigiTMG provides professional management and emerging technologies training across the globe. With international accreditations from world
renowned certification bodies, 360DigiTMG is at the forefront of delivering quality education,
thereby bridging the gap between academia and industry. For details please refer to our
website. Also please find my Linkedin Profile for your reference.