Demand for data scientist and analyst jobs has grown exponentially over the last few years. However, navigating the data science and analytics job market can still be confusing, given how job titles and descriptions do not always match up.

One of the key confusions are the differences and similarities between data analysts and scientists. This information is useful if you are interested in entering a data role and want to know what skills you need to pick up. On top of that, we also want to give you a snapshot of the local data scene and its members. How better to do this than to look at LinkedIn profiles?

In this project, UpLevel datanaut Bryan Tan examined the LinkedIn profiles of data scientists and analysts in Singapore using—wait for it—techniques in data analytics. We also used machine learning to see if we could tell the profiles apart from each other.

To the best of our knowledge, this is the first time anyone has attempted to examine LinkedIn profiles of data scientists and analysts who are based in Singapore.

Note: constantly saying "data analysts and scientists" is tedious so we'll shorten it to "DAaS" so daas better.

The approach