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Why Choose Data Science As A Career?

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Data science has become one of the most lucrative career options in India. There has been a considerable growth in the median salary to ₹16.8 lakhs per annum in 2022, up 25.4% from the previous year. This is 30.6% higher than that of an IT developer. Glassdoor has ranked data science as its topmost profession, which is mainly due to the exponential growth of data being generated. But what makes it so critical in all industries and why learn data science?

Making sense of the massive data chunks can lower business uncertainty. Data science does exactly this by monitoring, measuring and collecting performance measures to enhance the decision-making processes. Trend analysis can be used to improve consumer engagement, develop user-centric products and boost revenue as well.

You may consider a targeted data science course in case you are planning to become a business intelligence analyst, data analyst, data engineer, research analyst, analytics manager or data architect. The Data Science Architect Program offered by GeekLurn presents a well-designed course with excellent instructors and a 100% placement guarantee. With exposure to key tools and concepts, you will have expertise in Hadoop Development, Testing, Analysis Modules, Statistical Computing, Administration, Deep Learning, Artificial Intelligence (AI) and NoSQL applications after the successful completion of the program. The duration of the course is 24 months, which includes 6 months of live interactive classes, 18 months of sponsored project work and 320+ hours of live training sessions.

Why do you want to learn data science? Here’s a look at the reasons:

1. Demand and Supply 

Competition is less but demand has been growing. This is why you can choose data science as your career, especially if you have a quantitative background like finance. Studies have shown that there is a lack of ‘data literacy’ in the market since the data science field is still in a nascent stage. You may fill this gap by taking up a course. Apart from the core concepts, there are many subfields like computer science, statistics and mathematics. Once you join a job, you can become an independent decision maker and face less interference. This is mainly because you have a unique skillset with critical roles and responsibilities. All you will need are the right resources and direction.

2. Highest Salary Quotient 

The annual package is another answer to why data science. The salaries in this field range from ₹4.5 lakhs to ₹25 lakhs, with an average annual salary of ₹11 lakhs. Top skills like Python, SQL, deep learning, data science and machine learning are required. Data scientists are paid higher than other professionals in the tech community. It is an excellent industry if you wish to earn well, even at the beginning of your career. Perks include working on interesting tasks, freedom and flexibility, a chance to work for big brands and plenty of positions to fill with the ideal work-life balance. It is also a safe choice in the current environment; there are bound to be more opportunities as companies combat for customer attention.

3. Successful Career 

It is a broad field that is undergoing significant development and evolution. This explains why data science is important and the abundance of opportunities in this field. ML and AI combined with data science have the power to contribute significantly to intelligent decision making by organisations. This discipline is less likely to become obsolete since it discovers the potential of untapped markers too. For instance, Indian fintech company BharatPe used data analytics and AI to finance SMEs by estimating their creditworthiness. The company was able to disburse loans worth ₹3,000 crores with a repayment rate of 96%. There are similar other areas that have been identified and studied through data analytics. In short, data science will remain one of the rapidly growing industries for years to come. 

4. Complex Data Management

High-performance computing platforms can process vast oceans of data. This includes GPUs, TPAs and FPGAs. They can analyse and draw insights from data owing to advanced computational systems. Scientists also need large amounts of data to develop hypotheses, analyse market trends and draw inferences. Collecting, keeping and using data securely are other practices in the data science ecosystem. More and more industries are likely to be on the lookout for data analysis to make smarter and more targeted decisions. 

  1. Diverse Applications 

Data science is key for sectors like healthcare, education, gaming, digital marketing, airline route planning, augmented reality, speech recognition, internet search, fraud and risk detection and advanced image recognition. Other fields are human resources, marketing, finance and government programmes. The absence of quick computing and affordable storage can cripple these businesses, which would then need to invest hundreds of manhours to draw conclusions from the data being generated or miss out on opportunities to scale their operations and markets. Data science brings these systems into the world of AI and ML, leading to data-driven decisions. If you have been wondering how to learn data science, it is a good time to take the first step. Begin a course from a provider that is a member of NASSCOM and has partnered with IBM to bring you the best of knowledge and hands-on experience on projects.

The Bottom Line:

Learn data science to bridge your skill gap and secure a career that offers great prospects. You can work in an exciting field, where you will play a key role in developing smart solutions for businesses and become an indispensable part of the corporate world. 

Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.

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Neel Neeraj

Neel is a Product Manager with an interest in Data Science, Machine Learning, Cloud Computing, DevOps, and Blockchain with expertise in Python, R, Java, Power BI and Data analytics.
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