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Why is Data Science in Demand?
Why is Data Science in Demand?

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The author of the Indeed research and an economist at Indeed based in Austin, Texas, Andrew Flowers, claimed that the need for data scientists has only increased. "Data science professionals are in greater demand than ever among employers." According to research by Indeed, demand for data scientists has grown 344% since 2013 and by 29% annually.

 

Data from a technology job site similarly revealed that the number of data science job posts on its platform has surged by roughly 32% and that it considered data science to be a "high-demand expertise." The companies that are posting jobs come from a wide range of areas, not just technology. This is the reason many institutes have started offering data science training all over the world.

 

More than 3,200 positions are available each month due to a constant increase in demand for data scientists. Businesses thrive on using big data to help them make smarter business decisions even though they are aware of its value and power. $130,000 is the median base pay. The top skills include Python, R, Data Mining, and Machine Learning.

Why Data Science Experts are in Demand

I've included the top 6 reasons why data science is in demand right now in the list below.

  1. Businesses are having trouble managing their data.

Every day, businesses produce enormous amounts of data. Because of this, every business now has a tonne of data on hand and is unsure of what to do with it. They, therefore, need data scientists to manage this volume of data and derive useful insights from it

  1. Lack of knowledgeable resources

"There are two types of talent deficits: Analytics Consultants who can interpret and use data, and Data Scientists who can conduct analytics," explains Srikanth Velamakanni, co-founder and CEO of Fractal Analytics.

 

These job titles are in extremely high demand, and there is a severe lack of supply, particularly for Data Scientists. More than 150,000 data scientists are needed in the United States, according to a LinkedIn estimate from August 2018. Given how many prospective data scientists are entering the labor market, this supply-demand mismatch will undoubtedly be capped in size.

 

  1. Multi-factors are difficult to find

A basic understanding of at least one programming language is often demanded of data science practitioners; the two most common ones are Python and R.

In addition to expertise in statistical modeling, machine learning, and programming, data science experts are required to have knowledge of tools like Hadoop, Spark, and NoSQL.

More demand for SQL, Apache Spark, relational, and NoSQL database system expertise is being observed together with statistical and machine learning modeling. They are typically difficult to discover in a single professional in the sector.

 

  1. Obstacles to entry for other professionals

While some have degrees in business, economics, and social science, the majority of data science professionals have backgrounds in computer science, engineering, engineering technology, mathematics/statistics, and natural science.

Individuals who lack a foundation in arithmetic or computers may find it challenging.

 

  1. Excellent Pay

The compensation for the profession is also rising due to the increased demand for Data Scientists and other data science roles. Nowadays, this position has some of the highest compensation in the sector. According to Glassdoor, the average income for data scientists and analysts in the United States is above $62,000.

Experience has a significant impact on remuneration in India. Individuals with the necessary talents can make up to 19 lacs annually. Also, the average salary for an entry-level Data Scientist, IT, is Rs 619,182 annually.

 

  1. Offers Multiple Job Roles

Data science incorporates several fields, such as statistics, data analysis, machine learning, and software.

 

Data Scientist, Data Analyst, Data Architect, Business Analyst, Data Engineer, Database Administrator, Statistician, and Data and Analytics Manager are just a few of the highly sought-after positions. Data Scientists are among the highest-paid professionals in the data science industry and have one of the most in-demand job titles today.

US-based average salaries for various Data Science positions

Organizations are lavishly paying data science experts due to the requirement for data analysis and management.

 

  • Data scientist - $119,000 
  • Data Architecture - $100,000 
  • Financial Analyst - $65,000
  • Data analyst - $62,000 
  • Data engineer - $95,000 
  • Statistician - $75,000
  • Database Administrator - $68,000
  • Data Analytics Supervisor - $116,000

 

According to the IBM report, 59% of all data science positions are in the financial and insurance sectors, professional services, and IT.

Almost all corporate sectors that deal with data are relevant for the position, which includes every prosperous 21st-century company using big data in any capacity. They are in great demand since they are the decision-makers of the future for the business.

It's true that there is a great need, but as that demand has grown, so has the demand for data scientists. Yet, because of the rising demand in this industry, many people are focusing just on gaining the necessary abilities to enter the field.

 

This is why it's getting harder to hire people who aren't very experienced or who don't have any prior knowledge of the area. Finding a job in this profession has grown challenging due to a lack of knowledge among people regarding the practical aspect of data science.

 


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