According to The Analytics and Data Science Industry Study 2018 by Analytics India Magazine, the data science and big data industry in India is anticipated to grow 7x in the next 7 years, reaching $20 billion by 2025.
In accordance with the Talent Supply Index by Belong, the demand for data science professionals across various industries has increased by 417% in the last one year.
India is the second largest country to recruit professionals in the field of data science with more than 50,000 open job positions; the US being the first.
All these statistics speak for themselves. The data science industry is all set to unfold the careers of many professionals in India. Data Science hirings have become a competitive affair these days. Just like racers contend for pole position at a Grand Prix, tech companies are leaving no stone unturned to outdo each other to acquire and retain the best data science talent. Data science salaries or the work culture- competition is evident as countless start-ups and big players are in need of data science professionals, and they pay quite well too. This is one of the most exciting times for data science professionals to be alive and scoop up high paying jobs as the demand is not going to slow down any time soon.
Image Credit – TimesofIndia -8/5/2016
At Springboard, we have trained a lot of people with the skills needed to become a rockstar data scientist or data analyst. We get a lot of questions from aspiring data scientists about data science salaries –
“How much does a data scientist earn in India?”
“How much does an entry-level data scientist make?”
“How much can I earn as a senior data scientist in India?”
This has led us to believe that a discussion on the various factors affecting the data science salaries is a hot topic that we wanted to dig deeper into.
What are the various factors that influence the salary of a data scientist in India? At Springboard, we decided to identify multiple factors that might influence the data scientist salary – location, industry, years of experience, roles, and tools used so that professionals can maximize their data science salaries and work to their benefit as great enterprise data scientists. With all the factors affecting data scientist salaries, let’s finally get down talking to numbers.
Disclaimer – All salaries listed in this article have been collated from various sources Glassdoor, LinkedIn, PayScale, Indeed as references. This article is a simple guide on understanding the data science salary trends in India based on various factors like industry, experience, tools, role, and location. The actual salary that you will earn as a data scientist varies and will depend on a number of variables.
Data Scientist Salary by Role
Entry-Level Data Scientist Salary in India
Entry level data scientists are people who have just started out in the field of data science. They are the people who have heard about the awesome data science salaries, or might simply have one or more data science skills under their belt. Whatever the case may be, these people are seen as complete beginners with a very limited pool of information and no prior experience working in an organization. Entry-level data scientist salaries are rarely something “to dream for”. However, for an entry-level data scientist what should matter the most over the salary is the job title. According to PayScale, the average entry-level data scientist salary in India is 691,552. As a data science beginner, you should focus on learning and mastering the art of doing data science in the shortest amount of time possible; the increase in data scientist salary will follow.
Junior Data Scientist Salary in India
Junior data scientists are the people who have already devoted some time and research into data science. They might be university graduates who have already worked on a couple of data science projects or could be freelancers. Junior data scientists are usually considered quick learners as they already have the basic data science skills required for the job. All that they need to learn is how to successfully derive solutions for challenging business problems for the brand that they work for. According to Indeed.com, the average salary for a junior data scientist in India is 9,89,796.
Senior Data Scientist Salary in India
Finally, we have the senior data scientists – professionals who have been in the data science game for the larger parts of their lives. The title senior data scientist is somewhat self-explanatory; these data scientists have earned their reputation by mastering the art of doing data science fantastically. These are the people who are tasked with some of the highest priority tasks of a data science project. Considering the fact that senior data scientists are as knowledgeable about the company as they are, they are also tasked with overseeing the activities of newbies and junior data scientists. According to PayScale, the average senior data scientist salary in India is 17,49,792
Data Scientist Salary by Location
The location of the data scientist plays a vital role when it comes to finalizing the salary for a given data science project. There is definitely an added advantage to working in specific cities like Bengaluru, Mumbai, and Delhi which have a concentration of top data science talent and thriving tech companies. The most obvious pick for a rewarding and lucrative data science job is the Silicon Valley of India, Bengaluru, where top companies like Flipkart, Amazon, Myntra and other early-stage data science start-ups are headquartered. We’ve listed the top paying cities in India when it comes to a data scientist salary –
Data Scientist Salary by Experience and Degrees
According to LinkedIn Salary Insights, a Ph.D. degree can earn you an average salary of 20.7 lakhs while having a Master’s Degree without a Ph.D. will earn you an average salary of 10.2 lakhs.
LinkedIn indicates 1-5 years of experience is worth 11 lakhs or more, 6-14 years of experience is worth 20 lakhs or more, and more than 15 years of experience is worth 22.9 lakhs or more.
Data Scientist Salary by Industry
The industry you choose to work for can determine your salary as a data scientist in multiple ways. Each industry has its own challenges to tackle and therefore the pay for data scientists also varies. Choose to work for an industry you love and do not limit yourself by working in an industry where you cannot make the best use of your data science skills. LinkedIn Salary Insights reveal that the highest salaries are earned by data scientists working in the Banking and Financial Industry followed by Consumer Goods, Energy & Mining, Media & Communications, and Corporate Services.
Data Scientist Salary by Tools Used
The top skills that can have an impact on a data scientist salary are Python, R, Java, Statistical Analysis, SQL, Data Modelling, Machine Learning, Tableau, and a few others. Python and R are hot on the heels in the data science race with average salary packages starting from 12.75 lakhs. Professionals who have both data science and big data skill sets are likely to earn 26% more than professionals who just know data science or big data tools. Data science start-ups in India are cashing in on professionals with Python, R, & SQL skills while multi-national companies are still betting big in the data science game with expensive proprietary software like SAS.
Data Scientist Salary by Companies
We’ve included a list of some top tech companies with the minimum, average, and highest data scientist salary they pay from LinkedIn Salary Insights –
We have reached the end of this data scientist salary article. Becoming a proficient enterprise data scientist definitely requires a lot of effort and time spent learning and perfecting data science skills; something that you should be set on doing to pursue a rewarding data science career. However, if you are planning to learn data science, and are contemplating on taking the first step, we hope this article has given you some of the motivation to get started with learning data science.
Springboard offers a job-guarantee data science course that will make you proficient in data science tools and technologies used by Data Scientists. The course includes training on Statistics, Python, Visualization tools along with specializations in Deep Learning, Natural Language Processing, and Advanced Machine Learning.