Why Learn Data Science? 6 Reasons That Will Blow Your Mind

Why Learn Data Science? 6 Reasons That Will Blow Your Mind


This blog discusses the increasing significance of Data Science as one of the fastest-growing professions globally. It explores hiring trends in India's leading IT companies, emphasizing the high demand for Data Science professionals. The article highlights reasons to learn Data Science, including attractive salaries, exposure to various technologies, problem-solving appeal, flexibility, and job security due to the ongoing data revolution. 

Data Science is one of the fastest-growing professions in the world. This interdisciplinary domain is what helps organizations, small-scale to large-scale, to unearth critical business intelligence and make informed decisions. As the world gets increasingly digital, the relevance of Data Science has also become unstoppable. Read this article to find out why you need to learn Data Science right now. 

Points covered:

1. Data Science Hiring Trends at India's Premium IT Companies

2. Reasons to Learn Data Science

  1. Salary
  2. Exposure to technologies
  3. Appeals to Problem Solvers
  4. Flexibility
  5. Fewer Calculation Requirements
  6. Job Security

It’s nearly a decade since we’ve observed an uptrend in ‘data science hiring,’ as numerous companies have adopted or are in the process of adopting data science tools and techniques. Since there is significant growth in the applications of data science across industries, the century-old statistical methods collaborated with programming languages to evolve into what we know as Data Science today. 

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Hiring Trends

As Data Science becomes more relevant in the world and the data revolution seems to be getting stronger, the labour market has generated a great demand for Data Science professionals. Let's try looking at the hiring numbers of prominent IT companies based out of India. 

1. TCS

The company is coming up with new hiring terms wherein they are also looking for MSc and MA graduates, and not just engineering graduates for Data Science roles. TCS is positioned as a leader in data and analytical services by Everest Group. It consists of multiple data analysis services like TCS, Daezmo, TCS decision fabric, and TCS Dexam. As per their recent press release, they are hiring 40,000 people in the current fiscal year 2022-23.  

2. HCL

HCL Tech is paying higher increments and retention packages and expanding to tier 2 and tier 3 cities like Nagpur, Nasik, and Vijayawada. These are a few observations seen within HCL. In addition, HCL tech has multiple data analysis solutions like AI accelerator, model manager, smart buy, and hackthetale.  But as per a recent press release, HCL tech hires up to 40,000 to 45,000 freshers for this financial year 2023. 


Wipro has artificially augmented intelligence, business consulting, data, and analytics. On the other hand, Wipro is hiring 30,000 freshers for the year 2023, said Saurabh Govil, the President and CHRO of Wipro.


Infosys has multiple data analysis services related to applied AI, data analytics, blockchain, and IoT.  Infosys is hiring 30,000 freshers for the year 2023, said Salil Parekh, the company's CEO. The company employed more than 50,000 freshers in the last FY. 

Most of these companies are a significant part of data science hiring. Interestingly, most companies have a data science team in their organization, as most of these companies are focused on cost optimization and increased profit. 


What is Data Science? Why is Data Science Prevalent?

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Most of the concepts discussed in data science are nearly a century old. There were no good libraries and modules to execute them. The recent development in the data science field and the emergence of map-reduce in 2004, deep learning in 2006, the development of scikit-learn in 2007, and the introduction of spark in 2010 provided fuel for a vast array of possibilities that were adopted in areas such as supply chain, financial risk analysis, fraud analytics, marketing analytics self-driven cars and so on.

You may also want to read Data Science Career Roadmap for Beginners.

Data Science requires 3 skills: Coding, Statistics, and Business Knowledge. 

  • Coding - It is an important skill in data science wherein you must import, transform, manipulate, build and evaluate models using programming languages like Python, SQL, and others. However, you can switch to Data Science even if you are not from a coding background.  
  • Statistics - For a better data science model, you need to have a good understanding of statistics. At the same time, you need to know skills related to understanding the central tendency effect of the dependent variable on the independent variable, feature extraction, feature engineering, model building, and evaluation. 
  • Business - One also needs adequate knowledge of business and how it works, how to apply a data science model to a business, and how to bring efficiency into the process. 

You may also want to read Data Science Jobs in India.

Why is Data Science a Lucrative Career Path?

The following points explain why data science is a lucrative career path:

1. Salary  

As per the recent survey by Payscale, an entry-level data scientist is receiving 5,77,000 Rupees, including tips, bonuses, and overtime. Interestingly a person with 1 to 4 years of experience can draw over 8,00,000 Rupees.  

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2. Exposure to technologies

If you are a data scientist, you get an opportunity to work with multiple technologies like Spark, Python, and Big Data tools like hive, pig, Hadoop, power BI/tableau, etc.  As multiple skills are involved, you need to credible acquire hands-on experience.

3. Appeals to Problem Solvers

It goes without saying that organizations always have problems to tackle. The cutting-edge technology of Data Science is used to answer the right questions, extract valuable business insights, and make critical decisions. In short, if you’re a person who loves solving problems, this is the job you need. 

4. Great Flexibility

Data science is a huge umbrella of job roles like business analyst, data analyst, machine learning engineer, machine learning expert, data scientist, deep learning expert, head of analytics, analytical consultant, and so on. Whether you are planning to move vertically or horizontally, movement in Data Science is quite easy. For example, if you are working as a Data Analyst and want to switch roles to a business analyst, it is possible with minor skill changes. Similarly, if you have gained experience and want to grow vertically as a data scientist. you can!  

5. Fewer Calculation Requirements

Previously, calculating the mean of a list of values always meant manual work. If the data is huge, it can be really tedious to calculate the same value. But, with the introduction of Big Data and Python, it is much quicker and more efficient. As there is no need to calculate any value manually, a simple code you execute will perform even a complex calculation like a neural network.  

6. Job Security

In recent years, data science and the demand for skilled professionals have grown exponentially. This is going to remain so for the foreseeable future due to the ongoing data revolution. This will give rise to even more jobs in the market. The US Bureau of Labor Statistics predicts that there will be 11.5 million jobs in Data Science by 2026! In essence, now is the right time to kickstart your career in the domain of Data Science!

If you want to make the most of this status quo and launch your career in Data Science, sign up for OdinSchool's Data Science Course.


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About the Author

Please look at all the blogs written by a Data Science Subject Matter expert, Sangamesh KS.

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