Data science is one of the top fields of work in the US today, in terms of personal growth, career opportunities, and the subject’s contributions towards our progress into the future ahead. On top of that, an additional 27.9% growth in data science jobs has been predicted by the end of 2026, according to the US Bureau of Labor Statistics. So, on that note, we are going to go briefly over some of the most interesting and highly rewarding career options in data science, which also hold the most prospects right now.
Experienced data scientists can and most often easily earn more than what the national, mean salary for them suggests, but at roughly $125,000+ per year, that’s not a bad start to be inspired by! Their jobs do vary in accordance with the company that hire them, so we are going to point out a few key roles which they play within any organization next:
- Locating, identifying, cleaning, interpreting and organizing the necessary data sets
- Finding ways to make the data sets useful for the organization’s predefined goals, or that of the current project they are working on
- Using predictive modeling to suggest ways for strategically implementing the information recovered from the organized data sets
Being the most sought-after and important career in data science, only experienced professionals with at least an MS in Data Science can assume such a position. In case you already have experience working in the field, you will be happy to know that a Merrimack College Data Science Degree can be pursued online. Online courses like these are designed to be flexible for busy professionals, so they can be completed from anywhere in the world without you having to take a break from work.
Data engineers sometimes perform roles quite similar to data scientists, but more often than not, their primary role is that of forming data pipelines. They feed the data through a system that then reaches the data scientists, allowing them to work with the sets. They are the ones who are often found to be in charge of processing both raw and organized data.
Machine Learning Engineer
As we are discussing careers in data science that will shape the future, it would be impossible to not include AI engineering in this discussion. Now, it should first be mentioned that ML and AI are not synonymous, but they are closely related. Machine learning is a process through which an intelligent program or AI learns and improves its ability to take autonomous, correct decisions. Although it may seem like a machine learning engineer is more of an IT job than being part of data science, the truth is more complicated than that.
The job of the data scientist and the machine learning engineer are nearly identical in many ways, but there is a big difference. Being an expert in both data science and AI development, machine learning engineers focus on creating intelligent programs that can automate the whole process of predictive modeling. If an applications architect has the necessary understanding of AI engineering, they too can assume the role of a machine learning engineer or scientist.
It needs to be said that these are not the only jobs in data science that matter today, and there will definitely be more opportunities opening up in the future as well. The good news is, for someone who has completed their data science education with an advanced Master’s degree course, making the switch to a more lucrative branch within the field should not be particularly difficult.