Photo by Saulo Mohana on Unsplash
 

Did you know that 1.7 megabytes of data are generated for every person on Earth every second?

This colossal amount of data needs to be dealt with by specialists. Data science professionals know how to analyze and interpret data to extract insights to help businesses grow. 

It’s no wonder then that the job prospects in this industry are expected to rise much faster than in other occupations. There are only about 11400 data scientists in the United States, but the demand for their skills is increasing. 

 

Is Data Science Worth Considering?

 

Data science is a vast field that is still new, but it is already showing fantastic results. Dice report shows a 50% increase in employment opportunities for data science and engineering experts. 

Businesses in logistics, healthcare, finance, insurance, real estate, and transportation industries use data science, making it an essential part of growth. And for data analysis, you need a team of experts, software, and tools. 

You don’t have to be a data scientist to harness the potential of this growing industry. There are hundreds of employment opportunities and ways to specialize in big data. 

 

What Are the Benefits of Becoming a Data Scientist?

 

There are a good number of reasons to become a data scientist. The core benefits include:
 

High Demand, Low Supply

 

Data science is at an all-time high in the world. LinkedIn and other job-finding platforms are seeing increased data scientist job requirements. The appealing part is that a limited number of data scientists are available in the market.

Increased demand means increased wages. Companies know that there are limited numbers of data scientists, so they want to get the best talent as soon as possible. There are many job vacancies and internships available at any given time. 
 

Highly Paid Position

 

Data science is among the most highly paid jobs in the world. The average pay of a data scientist in the United States is $123,511/ year. There is also no denying that entry-level data scientists get good packages, and we can assume those with experience and in managing positions are paid very well. Managers can even earn more and have attractive benefits as well. 

Big data science projects have massive financial contracts. Find out which companies pay the highest to data scientists. 

 

Good Work-Life Balance

 

A data scientist can work on-site, remotely, or with hybrid work. The workload is comparatively small, and there is almost no need for overtime because of the nature of the work. Data scientists often work with software and tools on their laptops so they can complete tasks anywhere. 

Many companies hire remote workers too. Even when there is an on-site requirement, it usually is a 9 to 5 job with weekends off.

 

Learning Opportunities 

 

Data science offers immense knowledge and skills. We have mentioned above that the industry is rapidly growing and has huge demand. Almost all major industries in the world are adopting data science, and the need for filling data scientist positions is not stopping any time soon. 

Data science gives you valuable business knowledge and many essential skills necessary in professional life. Even if you plan to start your own business later on, your expertise with Big Data can undoubtedly come in handy. 

Moreover, sales staff can also benefit from data science expertise to enhance the efficiency of their sales pipeline and track consumer behavior.

 

Possible Challenges for the Data Science Industry

 

Apart from all the luxuries data scientists enjoy, there are some drawbacks and disadvantages you should be aware of if you are planning to shift your career to Data Science. 

 

There Isn’t a Set Definition of Data Science

 

Professionals argue about the nature of data science, and it does not have an exact definition. Some say it is statistics but redefined, while others consider it a proper pillar of science. 

Data science is a new field, so many explanations and reasoning are yet to come. The industry gives the role of a data scientist, but different industries can have different tasks and require different results. 

 

Becoming an Expert in Data Science Is Extremely Difficult

 

Data science combines mathematics, statistics, probability, and computer studies. These are tough subjects and even more challenging to master when building a career based on them. There are many gaps in mastering all the above fields - no one can have expertise in all areas at once. 

People can come from different backgrounds. A person who has expertise in computer studies may not have the same abilities in statistics. Therefore, data science is an ever-changing dynamic field of study where a person has to keep learning and evolving with the industry.

 

An Ocean of Knowledge Is Required

 

Even if a person has in-depth knowledge of computer science and statistics, there is still a possibility that they will not be able to solve data science problems without extensive training. 

For example, even if you have a background in IT and statistics, you’ll also have to learn a bit of coding. That’s because data scientists are often required to write algorithms in SQL, R, and other coding languages. 

Moreover, they have to run experiments to ensure their data is of the highest quality. Afterward, they clean datasets, and only then do they get to organize and structure data to analyze it. 

It’s a lot of work, and it’s all very new. So you can only make it in this industry if you are a self-starter and appreciate data for all the opportunities it can provide you with. 

 

Data Privacy and Arbitrary Results Are Tough To Deal With

 

Businesses take extreme measures to protect their data because of never-ending threats of cyberattacks and breaches that can compromise the data. Failure to adequately protect their systems can result in heavy losses. 

Data scientists are the first in the line of suspects when investigations happen since they interact with and secure data. 

A data scientist’s work is to study the data carefully and make near accurate predictions to facilitate the company. However, the data can often be arbitrary, so the results sometimes cannot meet expectations.

 

What Skills Are Required To Become a Data Scientist?

 

Becoming a data scientist requires many skills, including: 

• Machine Learning
• Data Analysis
• Deep learning 
• Mathematics
• Programming
• Multi-tasking
• Analytical analysis
• Problem Solving
• Data Manipulation
• Quick thinking 

 

Conclusion

 

We hope that this article has given you enough knowledge to help you decide whether you should quit your current job and become a data scientist. 

With the passing of time, data science has been evolving continuously. Although the challenges are complex, the benefits of being a data scientist are enormous. A highly skilled scientist may even eliminate the challenges data analytics faces today! 

 
 
Nahla Davies is a software developer and tech writer. Before devoting her work full time to technical writing, she managed — among other intriguing things — to serve as a lead programmer at an Inc. 5,000 experiential branding organization whose clients include Samsung, Time Warner, Netflix, and Sony.