4 Different Jobs You Can Have in Data Science

The tech industry is arguably one of the fastest growing and significant industries in existence. The world has long since begun to run on technology, and as time marches on, this trend shows no signs of slowing. With so much growth, it is no wonder that so many people who are proficient in computing and technology opt to enter the world of tech on a professional level.

The opportunities for employment in the tech industry are vast and, for the most part, incredibly lucrative. Job security and the potential for upward mobility make jobs in tech a hot commodity, too. From cybersecurity to software development, there are many different paths that you might consider taking with your career in tech. One such path that those with a knack for mathematics and programming choose to pursue is that of data science.

Data science is the computer science discipline that deals in the mining of data as well as in the building of our understanding of data as a whole. Such information is incredibly valuable and growing in value with each passing year. Algorithms, statistics, and machine learning all come into play for the data scientist.

Like all other areas of tech, the world of data science can be broken down into a variety of different jobs. If you feel that your calling lies in the pursuit of a career in data science, here are four such jobs that rank among the most popular with those in the data science field.

1. Machine Learning Engineer

In the field of data science, a machine learning engineer is responsible for designing and building specific types of machine learning systems. These systems are intended to funnel data or provide software-based solutions. The overarching job will require you to possess strong computer programing skills as well as a penchant for statistics. As the engineer of such programs, machine learning engineers are also responsible for the maintenance of the systems they build.

Because of the complexity of such a position and the demands of the job, many machine learning engineers choose to earn a master’s degree in data science after completing their bachelor’s degree. Such a step can help equip you with the practical knowledge and understanding of machine learning systems that you need to be successful.

The prospect of earning an advanced degree of this nature is an intimidating one for many people. The time and energy that is taken to complete your degree is certainly something that shouldn’t be taken lightly. That being said, there are many options out there, such as an online masters in data science, that can help you to achieve your goal of becoming a machine learning engineer without completely overwhelming yourself with trying to work full-time while earning your degree.

2. Data Architect

Much as the name of this job might imply, a data architect works in the construction, if you will, of data solutions. In addition to this main focus, data architects also work to improve upon existing systems to increase their performance and their functionality. The work of a data architect is done across multiple platforms, so a working knowledge of how systems run on various platforms is a must.

The average salary of a data architect is in the neighborhood of $108,000, making it an appealing job to go for. There is also a great deal of flexibility surrounding the types of businesses that you can choose to work with. You might wish to build systems for a company that works in finance.

There are also many options for data architects to work with healthcare-related entities as well. You will most likely wind up specializing in a particular industry so that you can provide solutions that are tailored to industry trends regarding the use of big data.

3. Business Intelligence Developer

If you have an interest in the world of business as well as the drive to work in data science, a career as a business intelligence (BI) developer might be a good fit for you. The job of a BI developer involves working with businesses to solve certain problems that might exist for that business.

As a BI developer, you will be responsible for taking the information that exists at a business in what is referred to as its business intelligence. The BI of a company consists of everything form marketing numbers to budgeting concerns. This data can be used to create the solutions that a company is after.

Since you would be working directly with a business or other entity, you will need to be able to communicate well as a BI developer. You will naturally need to collaborate with others involved in data science in some fashion to create the solutions that a company needs. Still, more importantly, you need to be able to take complex and technical information and relay it in an understandable way to your clients. This type of communication doesn’t come naturally to many people, but it is going to be part of the job if you wish to work as a BI developer.

4. Big Data Engineer

One of the highest paying jobs that exists in the world of data science is that of the big data engineer. Big data is the term used to describe data sets that are too large to be broken down, analyzed, and understood by traditional methods. Those who work with big data are charged with the task of understanding such data sets to obtain greater insights into trends and patterns of the human experience.

With such a tall order to fill, it is no wonder that big data engineers tend to pull in the big bucks. The world of business strives to gain insight into the consumer experience, and big data is one of the most valuable tools that help accomplish this goal. As a big data engineer, your primary purpose would be to transform big data into information that businesses can use in their efforts to generate growth and improve the overall consumer experience.

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