What will Data Science jobs look like in the future?

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What will Data Science jobs look like in the future?

Data Science in the future, indeed, is one of the most in-demand careers across the globe. In fact, every industry vertical needs a data science professional who can acquire, analyze and process available raw data to come to conclusions and guide business decisions.

Data Science in the future is an ever-evolving career field that demands its candidates acquire master’s level knowledge in programming languages, machine learning, data science skills, and business understanding to sustain in the competitive market.

For example, when you have a master’s level of expectations, you also various get higher-paying jobs like:

  1. Data Scientist 
  2. Data Analyst 
  3. Machine Learning Engineer
  4. Deep Learning Engineer
  5. Data Engineer

Statista’s forecasts suggest that by 2030 around 50 billion IoT devices will be in use around the world, with each device generating 90% of the world’s data in a couple of years.

Also Read: The future of customer service technology

That data can be used by Data analysts to obtain useful business information and help businesses to develop more. Likewise, trends like these attract today’s millennials and Gen Z to pursue Data Science. Let’s explore 5 more trends of Data Science. 

Read on!

Data Science has a wide range of use cases 

Above all, Data science is used by everyone. Not only the B2B or B2C industries like retail, manufacturing, and financial services, but small businesses like farming and non-profits also use Data Science.

In conclusion, this technical expertise has its contribution in every field from healthcare to FMCG to help improve operations, grow revenues, and enhance discovery for business development. 

Data Analytics serves a good range of career opportunities

Businesses around the globe can do wonders with the acquired data. As we know, data scientists invent new algorithms, and data engineers build the underlying infrastructures required to use data. On the other hand, a Data Analyst applies those algorithms to help business leaders make informed decisions to help grow businesses. 

Specializing in Data Analytics can help career advancement 

A working professional who wants to better his/ her output can specialize in Data Analytics. That is to say, this knowledge will help them tackle real-world problems and improve work quality. The tools of Data Analytics allow us to provide business insights, develop systematic models, perform various research and analytics activities, and produce intelligent reports.

Data can be used for storytelling 

Anything and everything that needs an analytical explanation- be it your office presentation or an article. Importantly, data can always be useful to convey your story. Data is a form of informative visual that can be presented through graphs or designs. Secondly, as the world has become more data-driven, it is important to make your data read or look more understandable. On the contrary, it is necessary to have a storytelling approach through data. 

‘Data literacy’ is equally crucial

In this paragraph, we are going to highlight the importance of how every working professional should know the importance of data in growing their business. Why businesses should use raw data, acquire new data and use them for business development? How will it benefit sales and help improve sales increase leads?

To sum it up, data science helps drive businesses to success. As a result, this makes it the most demanding career field. Most importantly, any data science job role you may pick, make sure that you walk along with the trends and be the industry leader. 

Want to explore more? 

Watch our expert Netali Agarwal, sharing her experience working as a Data Scientist at Infosys. 

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