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Data Science Jobs: What Makes the Job Hunt Intimidating?

I started off with Data Science Course in 2016 as a result of my curiosity about how apps like Amazon, Spotify and Netflix showed recommendations to the users. What captivated my attention there was the relevance of those recommendations to the users.

Clearly, there had to be excellent algorithms running in the background capturing all the actions a user did to reach a particular product, the order history, the location and various other parameters that guide a user to go and purchase a commodity; combine them all in a certain way and generate the recommendations for the users.

It was at this stage that I was exposed to the world of data science because Google said this is done with what they called recommender systems in the data world; one of the many fascinating applications of data science. Data Science is tremendously vast and what makes it more interesting is its spread to different expertise and domains.

Data Science cannot be done in isolation because it needs the knowledge of not one, not two subjects but an array of subjects which clearly cannot be done by one person unless that person happens to be Elon Musk or Jack Ma or someone from a Sci-fi movie.

On similar lines, Data Science Jobs are no different too because those jobs require knowledge from a variety of domains to get things done.

There cannot be just one position in an organization called a Data Scientist to handle all the data related activities of the project and also of the organization instead there has to be an array of professionals working towards the common goal as decided by the leaders and the organizational leadership.

This leads to the creation of a number of sub-roles in an organization for a data science project some of which are Machine Learning Engineer, Data Analyst, Data Engineer, Business Intelligence Analyst, Data Ware house architect, Business Analyst, Operations Analyst, Database Architect, Operations Analyst, Marketing analyst and the list goes on and on depending on the organizations.

No doubts however that choosing one of the many available options in data science can be unnerving at times and can be puzzling too. What makes it more confusing is the path ahead; the salary differences, the nature of work and the way they connect to form the chain that leads to the ultimate career option in data science; the Data Scientist.

Furthermore, what complicates the matter, even more, is the lack of knowledge on how well data science is doing in India, the future scope and what can one expect out of a data science project based out of the Indian ecosystem. All of these make the choices even more demanding and gruesome.

As mentioned above when I was first exposed to Data Science back in 2016, I had hundreds of questions giving me nightmares with the career option that I wanted to get into.

I was not assured whether changing my profile from a full-fledged technical consultant to a profile of a data science professional was a good idea because of the lack of knowledge in this particular domain. Some of the questions that popped inside my head while taking the decisions are as follows,

Is it a good idea to get into the data science field?

How exactly data science professionals help an organization with their strategies and planning?

Is India a good place for starting a career in date science or should I try opting the same in some other country?

What are the future prospects of the field? Is it promising? Will it give me enough resources and experience so that l advance in my career?

I am certain that it was not only me who was horrified with the career switch but many professionals and young brains have questions in the same line. To answer all of these questions in a nutshell, I would say, Yes, transitioning your career into data science and for young individuals getting into data science is perhaps the most intriguing change they can bring into their careers.

Data Science professionals are integral to an organization since they help organizations take data- driven decisions and informed risks. Data Science professionals are the pillars when leaders take key decisions in an organization and developing strategies for various processes in the organizations. Thus one can safely infer that in the coming years, there has to be a huge surge in the demands of data science professionals not only in India but globally.

Let us start understanding the scope of data science in India by looking at some of the statistics that was put forward recently. This should give us a clear idea whether getting a data science job is worth taking the career risks and whether the decision of getting into data science can be considered as the right decision. Below is a video by 365 Data Science, a famous YouTube channel for Data Science.

Looking forward to becoming a Data Scientist? Check out the Data Science Bootcamp Program and get certified today.

Data Science jobs: The Entrepreneur of the Present and the Future

If you are wondering as to how a data science job in India can be considered as the entrepreneur of the present and future, allow me to explain the same. As per the modern understanding of the word entrepreneur, it is someone who creates jobs and helps remove unemployment from a country. Data Science jobs do specifically this in terms of the employment opportunities it generates.

As per the Hindu, one of the leading newspapers in India, approximately 97,000 data science jobs lie vacant in India. In the recent years, an approximated increase of 45% of the jobs in the Indian market are attributed to data science. That means that almost half of the job postings that gets advertised in job seeking websites are indeed data science jobs.

Coming to the aspect that might interest many is the pay scale for a data science professional. India being one of the few countries in the world to give its services in varying domains such as medicine, healthcare, banking, pharmaceuticals, e-commerce, energy and the automotive industry, the demand for data science professionals are on the rise constantly for the last few years and will continue to grow in numbers in the future.

The average salary for someone getting started with this lucrative career ranges from 5L per annum to 7L annum depending on the organization type, the nature of the job and the sector. For someone with experience of around 5 years in the domain can earn as high as 15L per annum and someone with experience of 10 years and above with knowledge in different domains can expect a salary with the lower bound being 20L per annum which was very high compared to the conventional jobs in the IT industry.

The one factor that makes this field even more interesting is the gap between the demand and supply of professionals. It is probably because of the steep learning curve associated with this skillset and the constant upgrade the professionals have to go through in order to retain their relevance in the industry.

A Data Science job in general sense takes in a way lot more efforts than just getting a certification done or getting a masters in the field. Professionals have to be on the top of their skill sets at any point in time so that they can continue in the field of Data Science.

As per some of the leading job seeking websites such as Naukri.com; there is an approximate 25000+ jobs for the role of a data scientist and an estimated 14000+ jobs for the same role as per LinkedIn.

According to softscripts.com; there are an average of 2.3 million jobs posted in India in 2015 that went sky rocket to 2.9 million jobs by 2018.

All of these being under the umbrella of Data Science and categorized as Data Science Jobs.

Adding on to the scenario above, the existing conventional IT roles such as software developers, IT testers, testing engineers, system administrators, etc. have become obsolete with the advancement of the data driven world. Automation in these areas have reduced the roles to an extent that a comparison of the jobs in the last decade to the current generation job profiles leads to shocking results as we see many of the conventional roles have disappeared altogether from the IT industry.

Hence, the only savior for professionals in these areas is data driven technology. Data Science jobs are at the boom while conventional IT roles are declining day by day and we can expect them to become completely obsolete in the subsequent years to follow. And thus, professionals are expected to gain the competitive advantage by getting trained in the recent technologies especially the ones related to data science.

With this context in mind we can safely conclude that Data Science is indeed the entrepreneur of the present and the future. With the boom of analytics in the IT landscape, the recent generations and the upcoming generation will witness job openings that was unprecedented in the last decade.

Data Science Jobs: The Sexiest jobs in the current generation

According to Analytics India Magazine, below is the mean pay scale of a data science professional in various cities across India,

• Mumbai: 11.4L
• Bangalore: 10.3L
• New Delhi: 9.9L
• Pune: 8.8L
• Chennai: 8.4L
• Hyderabad: 8.3L

Mumbai, is known for its pay to digital innovators while Bangalore being the Startup hub of India has seen an unprecedented rise in the pay scale for a Data Science Professional.

Another very important factor which contributes significantly to high salary packages of a professional in Data Science is the gap between the demand and supply of skilled professional in the field.

As already mentioned above, the reason why data scientists are highly sought after are because of the reason that they possess a skillset which is not easily found by organizations and thus data science jobs often end up having a pay scale far more high and superior than most of the IT professionals.

The median salary for a data scientist in the early years is around 6.5L while the median salary of a software developer centers around 4.5L. Thus a professional who is into a data science job is highly paid and thus have more privileges and a higher salary to take back home.

Moving on, according to a survey by Analytics India Salary Study in 2020, experienced data science professionals had the privileges to demand higher salaries than their peers and thus the pay scale of experienced professionals are the highest registered in the last 4 years. The survey also throws light on the fact that data science jobs have seen a proportionate increase in the median annual salary packages of the professionals.

Getting deeper in the statistics of the salary of a data science professional, below is a highly detailed salary structure as per the years of experience of a professional,

• A fresher in a data science job with an entry level data science role earns an average salary of INR511,418 annually.
• A moderately experienced professional with years of experience varying between 1 year to 4 years, earns an average salary of INR771,130 annually.
• A mid-level experienced data science professional with years of experience between 5 to 9 years, earns an average salary of 12L-14L with an average of INR1,384,348 annually.
• A highly experienced professional in data science with more than a decade of experience in the industry and also having played key important managerial roles in the organization makes somewhere up to 24L annually. In some exceptional cases, such individuals are seen to make even 1Cr annually.

Moving on by adding another layer of information on the pay scale of a professional in a data science job, let us now see which skillsets offer what kind of salary packages for individuals.

• Professionals gaining expertise in programming languages like R and Python alone earn an average of INR 10.2L annually.
• Professionals who gain additional expertise in technologies such as Big Data and Data Science increase their pay scale almost by 25% of the salary package of someone who specializes in only one field.
• SPSS experts earn an average of INR 7.3L annually while SAS experts earn an average of INR9.1L -10.8L annually.
• Machine Learning professionals start with an annual salary of INR 3.5L annually which can reach as much as 16L annually with sufficient knowledge and expertise.
• Expanding the knowledge on the concepts of Artificial Intelligence increases the salary multi folds. For starters, they get a salary range between 5L –6L annually with this skill set.

Now that we have looked into the pay aspect of a professional involved in data science project from two different dimensions namely the years of experience and the different skills in data science, let us now turn our heads to the third dimension of the analysis; the pay scale by different organizations.

It can be safe to assume that the highest packages are offered by large MNCs whop are capable of generating huge amounts of data and are also capable of attracting clients that deal in huge chunks of data. What makes them even more convenient for working is that they have left a significant mark in the IT industries for increasing the pay scale year after year by almost 15%.

Here are some of the organizations as per upgrad.com that provide the industry best to individuals involved in various data science jobs,

• IBM Corp: INR1,468,040
• Accenture: INR1,986,586
• JP Morgan Chase and Co.: INR997,500
• American Express: INR1,350,000
• McKinsey and Company: INR1,080,000
• Impetus: INR1,900,000
• Wipro Technology: INR1,750,000

Looking at the overall picture, a career in data science looks quite promising because of the high salary packages and added privileges that an individual receives by being here. The shortage of resources and the scarcity of skilled professionals is what makes it far more lucrative and exciting.

And all of these coming from the single Nation, India; the career opportunities, the growth and pay scale in a data science job is far more rewarding considering the global industry.

Data Science Jobs: What does the Future Hold?

The key to understanding anything in terms of what lies next is to understand what has made the technology flourish so much in the first place. Looking at the history of a technology enables us to understand the patterns in which the technology has evolved in the past; the patterns, the challenges and the advances that still entail the technology in the present; the patterns which tell us how things will look like in the future and subsequently the patterns which would give us an idea how things will evolve in the near future and how fast the technology will be able to handle the advances.

Data Science in its entirety is not a new technology at all. The first formal attempt of having a data-driven technology was first introduced in the 1950s but what made them dormant then was the lack of data on which the algorithms would run and generate insights.

Almost all the algorithms in data analytics, machine learning and artificial intelligence are data-driven, i.e. to say they generate satisfactory results only when they are provided with data.

They are just a bunch of codes and semantics without appropriate data and that is one of the reasons why such sophisticated algorithms are made public and are community-driven, the real power of such algorithms comes into picture only if it is supplied with good quality data and a good quantity of data.

And hence, we make our first inference that more abundant the data is, the better are the results and with the growing technology we can expect an ever-increasing data size in the future which would generate more accurate results and predictions.

Hence, the future of data science jobs lies in safe hands when we consider the amount of data that is generated with the ever changing technological landscape in India and across continents.

Another way of looking at it would be the world before the data revolution and after the data revolution. Before the data revolution, the only data computers had to work with were structured data which were in very small chunks as a result they were analyzed very effectively with the traditional BI programs such as MS-Excel, PowerBI, etc.

Contrary to this, after the data revolution, data sets grew exponentially and also majority of this data was unstructured such as video files, audio files, tweets, comments, etc. which could not be analyzed using traditional BI tools as described above.

This called for a new technology and data science flourished.

With each passing day, the volume of unstructured data is increasing at an exponential pace and hence will call for more and more sophisticated data analytics algorithms and tools that would make analyzing this easier and less complicated.

Below are some of the trends that we can expect to flourish in the near future where data science might come handy with all its capabilities and analyzing power,

• At present, the Internet of Things has become a reality which enables us to connect everything that we use in our day to day life to the internet which in turn generates huge amount of data. In the near future, we can expect a similar paradigm where all the apps in our smartphones, televisions and other smart devices might be connected in a similar fashion thus working in tandem and generating more and more data which would add significant pressure on the already existing tools.

• Enhanced customer experience using intelligent chat-bots, Virtual reality and Augmented reality is likely to be seen in the near future. This is not completely in the future because we already see many websites and apps have embedded chat bots and many e-commerce websites such as Lenskart.com which deal in glasses and lenses already using these niche technologies enabling buyers to try the frames right from their computer screens with a 360 degree view of their faces. What the future holds might be in terms of enhanced customer experience including live simulations, on screen demos and visualizations of the products completely digitized.

• Newer technologies like block chain might gain popularity. At present, block chain is only used in the financial sector such as for bitcoins and other crypto currencies but we can expect block chain to spread its wings into other domains such as healthcare, banking, insurance, etc.

• We can expect an augmented predictive analysis in the future with the help of intelligent ML systems, automated systems and Augmented analytics to better the results that we obtain now with traditional data analytics and machine learning.

• Very similar to the other roles that dwell in the IT landscape, the data science jobs will undergo huge transformations in the near future to accommodate the ever changing landscape of the data science industry. This can be seen from the past where in the last decade or so there were no roles such as data analysts, marketing analysts, etc. but have now come into existence due to the boom of the data in the industry.

Data Science Jobs: How to get them?

Getting a Data Science job might look overwhelming at first because of the buzzwords that revolves around the core of being a data science professional. Generally, in India, the pathway to a data science job is not very different than getting into a data science job in abroad. However, data science jobs in India are particularly beneficial for the career advancement of a professional because of the shortage of skilled professionals in this field.

Getting into a Data Science job starts with getting a 4-years bachelor’s degree; however, if one wants to soar up the ladder through the various levels of an organization into a managerial position or generally speaking a leadership position in a data science project having a Master’s degree and a doctorate degree is a must. The common area of studies that enables an easy understanding of the underlying concepts of data science are as follows,

• Physics
• Mathematics
• Statistics
• Applied Mathematics
• Economics

Some of the academic institutions in India that provide courses in Data Analytics or Data Science are as follows,

• Indian Institute of Information Technology and Management, Kerala
• Indian Institute of Science, Bangalore
• National Institute of Securities Markets
• Indian Institute of Management, Kolkata
• Indian Institute of Technology, Hyderabad
• Indian Institute of Technology, Madras
• Indian Institute of Technology, Kharagpur
• Indian Institute of Information Technology, Delhi
• Jawaharlal Nehru University
• Ahmedabad University
• Academy of Maritime Education and Training
• Bharathiar University Coimbatore

Speaking specifically for the Indian market and Indian organizations, getting a Data Science job can also be attributed to short term courses and certification courses that exposes professionals and young graduates to the plethora of opportunities that data science has to offer them.

Some of the online courses which enables anyone to secure a Data Science job are as mentioned below,

• Data Science Specialization – JHU (Coursera)
• Introduction to Data Science – Metis
• Applied Data Science with Python Specialization – UMich (Coursera)
• Dataquest
• Statistics and Data Science MicroMasters – MIT (edx)
• CS109 Data Science – Harvard
• Python for Data Science and Machine Learning Bootcamp – Udemy
• Data Science Course by Henry Harvin (Click Here)

Thus, getting a Data Science job might sound scary but all that it takes is patience and curiosity for data. Getting a Bachelor’s degree is a basic requirement and also a good starting point but keeping oneself updated in the key to sustainability in the data science industry.

Data Science Jobs: Maybe it is not that intimidating after all

In a nutshell, it is safe to assume that Data Science is the technology of the future. Thus, getting into a Data Science Job is something that professionals should start considering given that many conventional roles in the IT industry will not exist for long.

In specific terms, India, the hub of IT services, getting into a Data Science job is more crucial than ever because of the constant shift in paradigm from a conventional decision-making process to a more sophisticated and trustworthy Data-Driven decision-making process.

India, in particular, is looking at the onset of a digital revolution that would change the IT industry forever with new job vacancies coming into existence in the data science field.

It is safe to conclude that Data Science jobs such as Data Analysts and Data Scientists are at their peak in the market and organizations are falling short of skilled workforce in the Data Science domain.

With the ever-increasing data set sizes due to the newer technologies such as Internet of Things and Social media, the demand for Data Science professionals is far more fetched than it ever was in the recent past. This includes a huge demand and supply gap towards the Data Science jobs and thus an increase in the salary packages for the handful of experts available for the industries.

Considering the future of Data Science jobs, the data will be ever-increasing; more specifically the data in the unstructured format which cannot be analyzed using traditional BI tools and hence the demand for Data Science professionals will be on the rise at least for several years to come.

Data Science is an evolving field with newer technologies and tools getting introduced at a horrendous rate. Data science jobs seem far from getting saturated in the next decade because of the ever-increasing opportunities and ever-changing data landscape in the industry.

In the years to come, one can expect a tremendous change in the Data Science Jobs, in terms of the remuneration, qualification and the nature of the work expected out of the professionals.

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