Data Scientists’ Salary In India: Expectations vs Reality
It is safe to say that Data Science is a field most in demand today, and is expected to rise even higher in the coming years. So, let’s dive right into what you can expect from a career in data science.
Data Scientists are experts who analyze company data to help solve complex problems and evaluate risks or develop strategies. These individuals are equipped with the two leading requirements for today’s world: Business and IT. They evaluate the need of the market and design models to eliminate risk, make predictions to develop strategies, bring modifications to provide a better user experience, and similar tasks. Because of the rising need to stay fit in the competition companies are in dire need to have at least one Data Scientist on board that helps keep the company’s ship stay afloat. And for this very reason, the job of a data scientist pays really well and is among the top highest paid jobs across the globe. The data science market, today, stands at $38 billion but is expected to go up to $140 billion by 2025. And as pointed out by Glassdoor, the average pay of a data scientist in India is Rs. 900,000 per year while that of a computer programmer is Rs. 400,000 per annum. This is a chief reason why data science is a career attracting fresh graduates.
Given the technological advancements today, capturing large data and analyzing has been made easy, but it does demand a whole lot of skills and expertise to stay updated and provide good service to a company, as a data scientist’s salary is highly related to their skillset. And so is the case in India, despite being the second largest country employing data scientists, having over 50,000 job vacancies, every company requires its employees to be the best there is. As per a report published by TOI, Mumbai and Bangalore are cities with high growth expected for data science job profiles, with salaries as high as Rs. 14-15 lakhs p.a. and working in companies like Accenture, IBM, TCS, etc.
What will your job include as a data scientist?
Understand the requirements and problems: It may sound like a really simple task but it really is not. Because how you understand the problem defines the solution and the further procedure so, it is really important that the problem is understood exactly like it is or it may lead to a huge waste of time, money, and effort. You should spend ample time in this step until you are sure that the situation and what you have understood from it are on the same page.
Gather data: Once the requirements are well understood, you are expected to collect all kinds of data that will help form the solution, including customer feedback, web scraping, interviews, etc.
Clean the data
This is considered the most time-consuming task of a data science project. Here, you need to clean noisy data, eradicate outliers, fill in or remove the missing value fields, manipulate data as per requirements, ensure all data is uniform in terms of field names and data types, etc. How well this step is executed determines the quality of the solution designed.
At this stage, a data scientist analyzes how the features of a data set behave and how they can be used. You also identify the relationship between various data values and recognize their use. Here, you gain some very important insight required for your solution.
This is a repetitive process where you go over the fields, again and again, to apply functions on the features and make the model performance stronger, by something like combining strong features and improving the model.
Building the model
This step is actually pretty fast but does demand a lot of planning. It is important to recognize whether the model is supposed to focus on speedy results or the quality of results provided.
Deploy the model
Now that the model is ready, all you need to do is deploy it for the company with the help of other domain members like ML engineers or data engineers.
Why does a career in data science look good?
Let’s look at the chief reasons for becoming a data scientist
High demand: As of 2020, data science is the most in-demand field and is predicted to offer about 11 million jobs by 2025 in a wide variety of companies.
Highly-paid roles: Due to its high demand today, it is given that the pay is not ordinary. With the salary as high as Rs. 15 lakhs per annum, this is not something that one would overlook.
Enhancing product quality: Using the methods of machine learning, companies are able to offer better and user-centric products that only make the customer experience better.
Advancing the workplace environment: WIth the use of AI and ML, mundane repetitive tasks have been automated by training the machines to perform those tasks using the human skill on jobs that require more creativity, critical thinking, and problem-solving methods.
Data Scientists Salary in India
Now that all other aspects are well understood, let’s understand the final determiner for choosing a career in data science: The Salary. So, the entry-level salary of a data science expert is usually around Rs. 500,000 and can go up to Rs. 15,00,000 with an improved skill set and more experience.
A data analyst with up to 4 years of experience earns around Rs. 4-6 lakhs p.a. Those with more experience, up to 9 years of experience are paid approximately Rs. 10,00,000 per year and those with a higher skill set and experience of more than 9 years earn around Rs. 15,00,000.
As compared to other highly paid professions, data science ranks around the second-highest-paid profession, as can be understood from the figure below.
But there are various factors that affect the salary, such as:
Location: Around India, the job opportunities and data scientist salary are highest in Mumbai, Bengaluru, and Chennai.
So, the location of the company does affect the salary you are offered. However, Bengaluru being the startup hub of India offers a lot more job opportunities. Also, the US offers an average salary of $96,072 and the UK of £40,159. The average data science salary as per location can be better understood with the following figure.
Experience: The correlation between years of work and salary is very prominent in the field of data science. An entry-level data scientist salary is averaged at around Rs. 5,00,000 with only theoretical knowledge and barely any real-time project application. These professionals are looking for their first data science project and focus on learning more.
With a little more experience ranging between 1 and 4 years, the salary goes up to approximately Rs. 7,50,000. Moving up in the experience scale, employees with experience between 5 to 9 years, have the potential to be paid anywhere between Rs. 12- 14 lakhs.
These Junior Data Scientists are generally flexible in salary and adaptive to the job profile. They come from a wide variety of academic backgrounds having different data science skills. The last category is the highly experienced professionals that have been working in this sector for 10 or more years, having been in managerial positions, are earning as much as Rs. 24,00,000.
This group of people have worked with several kinds such as stakeholders, customers, marketers, developers, in-house teams, etc. and thus know the in and out of almost the entire breadth of the company they work for. With a promotion, a data scientist’s salary rises by up to 50%. Due to the high demand for data scientists, many companies are offering internships too. Along with experience years, your willingness to work overtime, on holidays, etc. also affect your salary.
Skillset: To ensure a highly-paying job, you must be willing to go beyond just obtaining a degree and keep yourself updated with all the available programming languages that are required, the pros and cons of the possible methods and approaches, etc., generally speaking, be the best possible choice for the job as a Data Scientist.
The most crucial skill required for a high-paying job is being well versed with programming languages like R and Python. Besides Data Science knowledge, you must also know well about Big Data which is used to manage the huge amount of data that is used for analysis. Having a good command over the SPSS toolkit or even SAS is equally needed. Other skills that add to your salary are knowing how to work with Cloud Computing. But it must not be ignored that only knowing what these skills are is not going to help, you must know how to efficiently put them to use and get the best possible results.
Communication skills for a data scientist may not seem very important but it does help boost the numbers on your paycheck because a data scientist is expected to communicate with the stakeholders, customers, and even the entire hierarchy of colleagues.
Company: Well renowned companies do obviously lead the charts for highest-paying salaries to a data scientist. The industry domain of the company also determines the salary.
For example, companies that work with social networks, banking, cloud service industries, pay more than other industries like education and non-profit organizations. It is also not incorrect that the larger the company, the higher is the pay. So, a data science employee at Google can expect up to Rs. 1,10,75,000 roughly but those at some other smaller company earn about two-thirds of this.
So, we did go over almost all aspects of choosing data science as a career. But if a concrete job does not suit your interests, freelancing or interning is also a choice. Given the standing of the market today, data science would definitely not be a poor choice if that is where your interests lie.