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Although the title data scientist may be new and a little misleading, data science has been around for ages under titles, such as mathematicians, statisticians, quality analysts and more. However, over the last several years, data science as a discipline has emerged as a highly rewarding, yet challenging career.

With the development of mobile technology and mobile internet, the volume of data being generated is expanding at a remarkable rate. For instance, the world has about 3 Zettabytes of data as of now, but by the end of 2020, data volume is expected to reach, if not surpass 8 Zettabytes. Because of this new, vast amount of information, organizations have recognized the need for all different types of data analysis. But before getting into the different types of data scientists, what exactly is it?

Data Science – This far encompassing discipline combines computer science, machine learning, data analysis, statistics, and more. The title of Data Scientist is typically a blanket title used for roles that are often considerably different. Here are four types of data scientist careers.

Data Engineer – This data scientist is often brought on when a company gets to the point that they have an increasingly large amount of traffic and data that is needed for further progress and revenue, so they hire a data engineer to set up the data infrastructure. Because this role is one of the first to be employed by a company, there is a stronger emphasis on software engineering skills, rather than heavy statistics and machine learning.

Data Analyst – Once the data engineer has been hired and has begun working on the infrastructure, a data analyst is brought on to pull the data, create data visualizations and reporting dashboards, and even take on the company’s Google Analytics account.

Machine Learning Engineer – In some companies, the data is the product. In these consumer-facing cases, the massive amounts of data are extraordinarily expansive and call for someone with a more formal, academic background in mathematics, statistics, and physics. Of all the data scientist positions, the machine learning engineer requires the highest level of expertise. In fact, senior scientists have learned to automate mundane tasks.