Data Analyst, Scientist and Engineer

easter nest three

Hello everyone!

A while back I wrote about what a Data Scientist is. When you are scrolling through Data Science jobs, you might also find postings for jobs as Data Analyst or Data Engineer. Obviously, all three are related to Data Science but what exactly do those job profiles mean? Let’s find out together!

The title does sound like a joke… an Analyst, a Scientist and an Engineer walk into a bar… if you know how the joke ends, let me know down below in the comments 😉

All three work together on the mission to get information from data… so how do they differ? Actually, there are no clear boundaries between the job descriptions. But the core of their work is still different from each other.

The Data Analyst
What does a Data Analyst do?

A Data Analyst does the “classical data analysis”. Still, this is a very broad term. To me, this means that the Data Analyst gets a set of data and then transforms the set in such a way that useful information can be extracted.  This is still feasible on one computer.

Others might make a decision based on the information hidden in the data. Therefore the Data Analyst has to visualize and present the data in a suitable way. I imagen that the Data Analyst might not be an expert in the field he is evaluating data for. For example, if you are working within a pharmaceutical company, you might not be an expert on chemics or such. So you will need to get some information about what the data is about. Which means talking to people and learning from them. Only if the Analyst knows what the data stands for and has a good understanding of this,  he or she will be able to judge whether the pieces of information found make sense. Also, you want to add value with the analysis, so you need to know what influences what and for that, you need some knowledge of the subject which “created” the data in the first place.

Educational Background

What does it take to become an Analyst? I checked some job postings for this, to see what the “industry” or “market” is requiring. There is no “one” requirement that they all hold. Which kind of astonishes me. Though it is almost everytime asked for at least some background knowledge of the field in which the employer is active. Those were some things that employers were looking for:

  • analytical way of thinking
  • ability to work on projects
  • experience/knowledge in statistical and mathematical analysis and modelling techniques (aka statistics and math)
  • programming skills to perform statistical modelling (e.g. R or SAS)
  • handling relational databases (e.g. SQL)
  • skills in data visualization (for example tableau or d3.js)
The Data Scientist
What does a Data Scientist do?

A Data Scientist, like the Data Analyst, also extracts information from data. For me, the Scientist works more with big data. It’s also the Scientists job to work with Artifical Intelligence and Machine Learning. While the Data Analyst might focus more on describing the data and deriving information from that, the scientist tends to use predictive models.

Again, based on the information provided by the Scientist, decisions will be made. So for one, of course, the Scientist will also have to have a certain knowledge of the field. But also does he or she have to communicate the results in a clear way. So the people who make decisions make them on the right base. Sometimes this is harder than one would imagine.

Educational Background

Here are some things that were asked for by employers in a Data Scientist:

  • Bachelor, Master or PhD in either Computer Science, Statistics, Mathematics, Engineering, Economics or Physics
  • Experience/Knowledge working with large data sets and tools like Hadoop/Spark
  • Coding skills in Python, SQL, SAS, R or similar
  • Expertise in Text Mining and Natural Language Processing
  • skills in data visualization (for example tableau or d3.js)
The Data Engineer
What does a Data Engineer do?

Neither Data Analyst nor Scientist would have an easy life if it wasn’t for the Data Engineer. The Data Engineer is responsible for collecting and storing data and for maintaining the databases. This might sound easy, but it is not.

A Data Engineer is sometimes also called a Data Architect. Which I feel describes quite nicely what he does. He or she creates and maintains a home for the data. The Engineer/Architect creates scalable database and -flow architectures and improves the IT infrastructure. He or she is also taking a look at matters such as security.

Educational Background

What does an employer expect from a Data Engineer? Here are some things I have seen while browsing some jobs postings for Data Engineer or Data Architect:

  • degree in Computer Engineering or related field
  • focus on developing high-quality software
  • versed in Scala and/or Java
  • familiar with cloud computing services
  • skills/experience in database management systems
  • knowledge in data model and data flow for database structures
To sum up

As I mentioned in the beginning, these three jobs sometimes overlap and there really is no clear definition. Depending on the company they might even have different names.

I hope this was informative for you! Let me know down below in the comments, if you are working in the field and if you feel that I forgot something 🙂

Thank you for reading!


P.S. I initially wanted to use this picture for the post, but then I thought “oh well it is easter so I want to use something more eastery”. But I do think this picture is just too good not to put in the post 🙂

One thought on “Data Analyst, Scientist and Engineer”

Leave a Reply

Your e-mail address will not be published. Required fields are marked *