What REALLY is Data Science? Told by An Ex-Microsoft/FAANG Data Scientist

Data science, is it about designing models and creating cool visualizations with D3? Not really. At least, it’s not your Goal.

But don’t take our word for it. We recently found a great channel on youtube created by a Youtuber named Joma. Joma’s full name isJonathan Ma and he has worked at several big tech companies including Microsoft and a FAANG. He will go over this more in the video. But, just to summarize some of what he talks about. Data science is about impacting your business with data. Now, does that often require models, and visualizations. Yes.

But when you focus on the tools, you aren’t focused on what you are trying to build.

Solving real company problems don’t always require the newest tech. Now, I know, some of you out there are probably getting upset.

“No, you don’t understand, data science is a research position. It always requires a PhD. You have to know 8 different programming languages and have at least a masters in statistics and have written at least 10 research papers”

And in some cases that is true. In fact, Joma does a great job of breaking down how different size companies will often need data scientists with different skill sets. A small or a medium size company will often need a much more experienced data scientist with a PhD and lots of technical knowledge. This is because they can only afford a few data scientists so the ones they do have need to be “stallions” to take a snippet from Silicon Valley. Where as a large company might be able to break up the work more so they could hire 1 PhD to do the very research dependent work and then hire other less experienced data scientist to do the analytical work. We will let Joma take it from here.

It can be hard to get past the hype of data science. We see self driving cars or hear about cool models implemented by start ups and think, that is what we are going to do. But often times, it is not needed or is done by a specialized set of data scientists.

Data science is a very exciting and broad field, but we want you to know what you are getting into. Many people just shrug off the fact that data scientist really do spend most of their time gathering and cleaning data, they shrug off the fact that you might not need to use all the complex models you learned in school, until you are actually in the workforce.

It’s ok if you don’t. Software engineers don’t often use much of what they learned, nor do many other majors. But, it doesn’t mean we aren’t doing meaningful work.

Thanks so much for reading. We do hope you enjoyed the video, we did! And if you’re still interested in the tech field check out the experiences Joma had when he was trying to break into the field.

For further reading and videos on data science, SQL and Python:

How Algorithms Can Become Unethical and Biased

How To Load Multiple Files With SQL

How To Develop Robust Algorithms

Dynamically Bulk Inserting CSV Data Into A SQL Server

4 Must Have Skills For Data Scientists

SQL Best Practices — Designing An ETL Video

Learning Data Science: Our Favorite Data Science Resources From Free To Not