Those who have decided to find a career working with data have already made a wise choice. The number of jobs for data scientists alone is expected to jump 19% by 2026, according to the Bureau of Labor Statistics.
But that raises a question. What, exactly, does a data scientist do? And how is that different from the work of a data engineer or data analyst?
It’s a question worth asking. For those planning to earn a degree in one of these fields, it’s important to know which one best matches your skills and interests. Here’s a look at all three professions, including the typical job duties for each.
This is the job where many of those who work in data start.
A data analyst typically does not create new algorithms, but rather works under the direction of more experienced analysts or data scientists in a junior role. They will need strong technical skills in programming, the application of statistical models, machine learning and data visualization. The ability to presenting data findings in a way that is accessible to those without expert-level technical skills is also key to this position.
In addition to preparing data visualizations, a data analyst may also be tasked with cleaning data and making it useful for analysis. Their work might be used in situations where executives want to understand the data behind a recent growth or reduction of business. Or, for marketing teams looking for the right demographics to target with a new marketing campaign. Data analysts may also work with the cybersecurity team to identify weaknesses and potential risks.
In short, they look for trends in data that can prove beneficial to an organization, but under the direction of a manager.
While the job might sound similar to that of an analyst, data scientists delve deeper into larger datasets and more complex issues using advanced data analysis tools.
They typically have a graduate-level degree in a data-related field such as applied mathematics, computer science and physics. They are often handed open-ended challenges that they resolve, unsupervised, using advanced data techniques. They may write new algorithms themselves for machine learning models.
Where a data analyst might look at data from a single source, a data scientist uses multiple sources of information and finds how they relate. They often are not so much focused on past or current data, but on building predictive models to map out potential future events based on various business options.
If data analysts and data scientists are to do the analytical work their positions demand, a good data engineer will have to first provide them the tools to do so.
Data engineers focus on constructing the databases and data pipelines that can handle the massive amounts of data that analysts and scientists will use. They are more like software developers, building the foundation upon which analysts and scientists will do their work.
A data engineer’s job can vary depending on the organization. In addition to building a system’s architecture, many also are tasked with managing a large database. They also will make sure the system fulfills all requirements and is made with the necessary security measures to protect data integrity. Having an advanced degree in database administration can be a step in the data engineer’s career.
Each of the three jobs has an important role in the data-driven business world of today. All three also present solid career paths and large potential for job growth. Which one is the right path to follow depends on each person’s skill set and interests.