Who earns more, data scientists or MBAs?

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The job market for data scientists and MBA

The demand and job market for skilled data scientists are skyrocketing because every company and business requires data scientists to make better informed and data-driven decisions that can keep the business ahead of the competition. Organizations look for experienced data scientists who can derive insights from data and enable them to perform thorough data analysis. Demand for MBA professionals is also growing, however, at a slower rate. Companies look for MBAs who can manage their business operation and help them frame strategic decisions.

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Scope in MBA and data science

After completing an MBA degree course, a lot of career opportunities will open up in front of you. From leadership roles to executive rule, project managers, marketing managers, etc. MBA professionals can also fill senior leadership roles in their careers. Their leadership and management roles are in massive demand by organizations and companies that want to manage business confidence, marketing, sales, human resources, etcetera departments. In addition, the profitability and success of a company will depend on MBA leaders who can make better decisions for the organization. 

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On the other hand, data science freshers and graduates are in massive demand in the present economy since they are trained professionals in mathematics, computer science, and statistics. These professionals derive customer behavior, hidden trends, and patterns from massive data sets. 

What are the educational requirements for MBA and data scientist?

The educational criteria for an MBA and a data scientist differ from one another. A data scientist is required to have a minimum bachelor’s degree in the following field

• Mathematics 
• Computer Science 
• Information Technology 
• Statistics 

Many employers also seek advanced or master’s degrees in data science as the field is quite competitive. On the other hand, the educational criteria for an MBA require professionals to hold a minimum bachelor’s degree in economics, science, business, or any other related field from a well-recognized university.

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What skills are required to succeed in the data science and MBA field?

Data scientists are required to have robust data interpretation and analytical skills so that they can predict data accurately. These professionals are also required to have the problem-solving aptitude, good communication skills, and the capability to work with models and algorithms for solving complex business problems. An MBA professional, on the other hand, must have good business acumen and strong domain knowledge to frame strategic decisions on the basis of financial and economic data analysis. Finally, MBA professionals have to communicate their ideas and strategies to decision-makers.

According to Glassdoor reports, the average annual salary for a data scientist in the United States is around $113309 every year. The exact salary of a data scientist will depend on various factors, such as location, company, and the candidate’s experience. As per Glassdoor reports, the average annual salary of an MBA in the United States accounts for $102867. These statistics clearly reveal that a data scientist earns more salary compared to an MBA because of the diversity of their work. Not only do data scientists enjoy higher salaries, but their job outlook also looks positive because of the increasing demand for better and more data-driven decisions that these professionals make for the business. Both MBA and data scientists are offered rewarding salaries in their careers depending on their location and experience. However, data scientists are comparatively higher in demand and enjoy higher salary packages. It depends on your preferences and career goals which profession will suit you. 

Why are data scientists paid higher than other occupations?

Shortage of talent

One prime reason why data scientists enjoy a higher salary than an MBA is because of a steep shortage of data science talent in the market. Even though job opportunities and demand for skilled data scientists are constantly increasing, skilled professionals are lacking to fill the emerging job role. As a result, companies worldwide can reap numerous benefits by employing data science professionals, from small-sized companies to large corporations. 

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Difficult Work

The work of a data scientist is not a mere cakewalk. Data scientists have to perform challenging tasks and work with complex algorithms and models to make accurate predictions for the organization. In addition, a data scientist has to perform many rules, such as working with the computer throughout the day, sorting a lot of data, use the correct mathematical and statistical techniques to accomplish all the objectives. All these reasons justify why data scientists are paid higher than other occupations.

Work with cutting-edge tools and technologies.

Data scientists require years of practice and practical knowledge to make predictions out of data. Moreover, these professionals must upskill and update themselves as new technologies and tools keep changing and updating.