Welcome back! Data Science and Software Engineering have their similarities and differences, they both are programming intensive and a lot of the work can be overlapped on both positions. However, let’s discuss the main differences between a Data Scientist and a Software Engineer.
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There are actually quite a few similarities between both fields, they're both programming intensive and they both involve a lot of the same tools. In my personal life, i’ve seen many Software Engineers become Data Scientist and vice versa, so there is quite a bit of overlap between both fields. Let’s take a look at the average salaries between both fields:
On GlassDoor, the average Data Scientist salary is around $114,673 a year:
GlassDoor also mentions that the average Software Engineer salary is around $104,749 a year:
So in terms of a salary stand point, there is actually little difference. To be completely honest, i’ve heard of many people’s salaries being much higher than this for both positions, so I don’t think I would choose one position over the other from a salary stand point.
Another massive thing when looking between these two positions are the available jobs out there, if we take a look at Indeed.com, we can see that they estimate that there are over 24,000 jobs available in the United States right now for Data Scientists:
Doing the same search for software engineering, we can see that there are over 120,000 jobs available for this position:
This is by far is one of the biggest differences between these 2 positions, technically, you have more jobs to apply for as a Software Engineer than a Data Scientist. This is what I would say about this, if you love Data Science then by all means go down that road, I would recommend creating a bunch of projects, blogs, Github projects, etc. to make yourself stand out, the same thing goes if you want to become a Software Engineer.
The work flow is also pretty different from a Software Engineer and a Data Scientist, although both are programmers, the tech stack between a Data Scientist and a Software Engineer tend to go like this:
Able to create analysis of different data sets, ranging from data processing, data engineering and machine learning development using different programming languages (Python, R, SQL, MATLAB, Scala, etc.).
Again, this is a pretty brief overview, but it allows you to see some of the different programming languages you may need to use between both. One definitely isn’t anymore superior or easier than the other one, so leveraging your knowledge in those languages can help you make a decision. From my experience, you will still need to understand a bit of database development for both (obviously a bit more for Data Science), as well as Cloud development experience (AWS, Google Cloud Services, etc.).
The main takeaway here is to find out which specific programming languages you enjoy / what you tend to do the most with in your projects. I would recommend looking at different beginner projects for both Data Science and Software Engineering, if you find out that you enjoy creating different machine learning models, database development or any sort of data processing then by all means focus on Data Science, but if you find yourself creating applications, web development or enjoy developing out the front end of a project, then Software Engineering maybe the better choice for you.
One position isn’t better than the other one for everyone, but one might be better for you. As I stated before, the main difference from a standard “job” perspective is that there are definitely more Software Engineering jobs than Data Science positions, so if you don’t care about anything else that maybe a better choice for you, but if you love Data Science than by all means apply for those positions. The salaries seem to be about the same, they’re both programming intensive and they’re both very technical, so no matter which position you choose, you will definitely be able to tune your programming skills and have a very rewarding career for sure!