All You Need to Know to Make a Career Switch to Data Science

Data Science is one of the most talked-about domains in the world today. Driven by data, organizations can make the best business decisions during the most crucial times. From data, companies can gain key insights about their customers, markets, and their own performance.

Artificial Intelligence (AI) and Machine Learning (ML), too, are heavily dependent on data and Data Science in general. This includes processes such as data sourcing, data mining, data cleaning, dataset preparation, and data modelling.

As and how AI and machine learning are finding increasing adoption, forecasting and automating processes has become easy for businesses. AI has been known to increase the performance of businesses globally, and also helps provide customers with a better experience. This is leading to the increasing dependency on AI and machine learning for both large enterprises and smaller businesses.

Data scientists are crucial for projects that are AI or ML based. Let’s take an example of a music recommendation system such as Spotify, where the AI must learn how to recommend relevant songs to the user. A big chunk of the project would be data-based, where the system is taught to identify patterns in the user’s listening history and recommend songs that would be in line with their listening tastes.

Another example is using machine learning for customer sentiment analysis or predictive analysis, where data scientists are absolutely essential to process the data and run it for the analysis. To have an edge over the competition, it is critical for businesses to use these ML-driven systems. The need for data professionals for job roles such as data engineer, data scientist, and AI-related roles is only going to increase in the coming years.

The global market for Data Science has been estimated to reach $140.9 billion by 2024 with a CAGR (Compound Annual Growth Rate) of 30%. Data Science is currently one of the most valuable domains in the IT sector. Hence we see a strong scope of Data Science in India, with exciting opportunities ahead.

Roles such as Data Engineering, Data Analytics, and Cloud Computing are related to Data Science. The career prospects are endless for data science professionals and there is even an ample amount of scope of applying Data Science knowledge and skills in other functions such as finance, marketing, supply chain, operations, sales, customer experience, HR, and more.

Top reasons why switching to a data science career makes sense

Data Science is an incredibly vast and interesting domain. This field comprises several job roles to cater to the interests of different individuals. For example, you can choose to work in analytics and help companies gain insights from data.

Or, if you do not wish to directly be involved with business intelligence and data-driven strategies, you can simply help develop AI-based systems. All kinds of development processes, especially ML-based projects, heavily rely on well-curated datasets.

More than anything, the data sourcing and the data architecture should be sustainable and compliant. The role of data science professionals is absolutely critical in modeling data and systems.

Data Science job roles are fun and also offer incredible job satisfaction. Data scientists and all other data science professionals hold important positions  in key projects and their organizations, and this factor itself allows individuals to take pride in their work. Moving away from the fun side of things, let us now understand why switching to Data Science can be beneficial for your career.

Here are the top 6 reasons that justify switching to a Data Science career:

Data Science is an extremely valuable sector

By 2025, it is estimated that we will have generated over 163 zettabytes of data. And this estimation was made before the Covid 19 pandemic, probably implying that the total data we generate might cross well over that number. The pandemic has forced more businesses and functional processes to move fully online, thus, accelerating digitization.

According to Business Wire, the Data Science market was valued at $43.3 billion in 2021, which is already incredible. However, based on the estimates by Mordor Intelligence, the value of this domain will rise to $230.8 billion by 2026 (39.7% CAGR). This is almost a 5 times increase in just 5 years of time.

Data Science does not just help companies analyze, store and manage data. With the ability to incorporate AI, businesses are able to scale themselves and serve more customers. With automation being a very lucrative sector as well, Data Science is only growing in value.

1. Great opportunities and career growth:

Data Science has a number of opportunities and a huge number of vacancies. For instance, a quick search on LinkedIn for Data Science jobs would fetch you thousands of results at any given time. There is also a lot of scope in terms of career ascension as companies always wish to acquire senior data science professionals for sensitive projects.

This is especially true for core operations, as minor errors in data preparation or strategy can cost companies a lot of money. According to IBM, the need for data scientists would grow exponentially in the coming years. In 2021, there were about 1,37,870 open jobs in Data Science in India.

In Data Analytics alone, there was a 47.1% increase in vacancies from 2020 to 2021. And in terms of growth, you can become a Senior Data Scientist in around 5 to 9 years. Once you complete 10 to 19 years of service in this sector, you can become the Director or Vice-President of Data Science in an organization.

2. Diverse job roles and plenty of scopes to get into other related domains:

Data Science consists of a multitude of job roles that range from visualizing, presenting, business intelligence, analysis, developing, reporting, forecasting, and dozens more. All of these job roles are equally valuable, and it is completely up to you to decide upon the kind of work you wish to do on a daily basis. Data Science is an excellent domain in terms of choices and options.

You can also choose to be an AI engineer, ML engineer, data architect, data engineer, database administrator, or business intelligence developer. Cloud computing is another related domain, and you can also choose to become a cloud architect or cloud engineer later on as well.

3. Great Salaries:

The average salary of a Data Scientist in India is a respectable amount of  ₹8,60,316 annually. Meanwhile, the average data scientist’s fresher salary in India (with 1 or less than 1 year of experience) is  ₹5,71,493 per annum.

Data Scientists who have 1 to 4 years of experience earn  ₹8,00,750 annually on average, while more experienced Data Scientists with 5 to 9 years of experience earn  ₹14,20,229 on average per annum. Finally, veteran data scientists with more than 10 years of work experience earn an average of ₹18,40,360 per annum.

Additionally, the average salaries of a Data Analyst and a Data Engineer in India are ₹4,56,667 and ₹8,57,779 per annum, respectively. Large organizations and conglomerates in India also pay their data science professionals very well. For example, Microsoft, Amazon, Google, Deloitte, IBM and Accenture pay an average of ₹16,00,000, ₹14,68,285, ₹14,62,754, ₹12,76,245, ₹11,28,733 and ₹ 10,00,329 respectively (per annum).

4. Data Science is open to professionals of different academic backgrounds:

Data Science is not necessarily limited to individuals who come from the Computer Science background. It also helps if one has a strong foundation in mathematics and statistics; however, the necessary concepts and algorithms can also be learned in a realistic period of time. Other abilities such as being able to use analytics tools, DBMS, distributed file systems and programming languages such as Python or R can all be acquired in a few months to a year and a half at most.

5. Learning Data Science has become very easy and accessible:

Learning Data Science tools and skills has become incredibly easy with the help of short Data Science online courses or expansive Data Science certification programs. Even without a Data Science online course, you can choose to learn any of the associated tools or programming languages through written tutorials, academic resources, and videos. So, if your concern is how to get into a data science career, you can get started by acquiring the skills to do so.

So, is the average Data Science career in India lucrative? Yes, absolutely. Data Science pays well and offers job security plus career growth in the long term. For both freshers and professionals, switching your careers to Data Science is incredibly beneficial for your future.

Data Science, as a sector, has a lot of potential, and we have just managed to uncover the tip of it. If you enjoy solving problems and love data-driven methodologies, you should definitely go for Data Science.

Learn crucial Data Science skills and future-proof your career. Check out Hero Vired’s Integrated Program in Data Science, Machine Learning, and Artificial Intelligence to find out more about how you can get involved with Data Science.