5 career trends in Data Science
Data Science in Future, indeed, is one of the most in-demand careers across the globe. 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 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.
With the master’s level of expectations also come higher salary paying jobs like:
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Deep Learning Engineer
- 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. Trends like these attract today’s millennials and Gen Z to pursue Data Science. Let’s explore 5 more trends of Data Science.
Data Science has a wide range of use cases
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. 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. While data scientists invent new algorithms and data engineers build the underlying infrastructures required to use data, a data analyst can apply those algorithms to help business leaders interpret data and make the decisions that help grow the business.
Specializing in Data Analytics can help career advancement
A working professional who wants to better his/ her output can specialize in Data Analytics. 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, data can be used to convey your story. Data is a form of informative visual that can be presented through graphs or designs. As the world has become more data-driven, it is important to make your data read or look more understandable. So, a storytelling approach through data is important.
‘Data literacy’ is equally crucial
Before applying the science of data analytics, every working professional regardless of the domain should know the importance of data. 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, all these questions should be answered by every working professional.
Simply put, business success drives data science and so data science is one of the most demanding career fields around the globe. Any data science job role you may pick, but make sure that you walk along with the trends and be the industry leader.
Want to explore more?
Then watch Netali Agarwal, sharing her experience working as a Data Scientist at Infosys.