The 5 High Demanding Data Science Roles

That you should know about…

In this post, I would like to share the top five data science careers that are in high demand these days. Data Science field is growing so fast that it’s getting harder to keep track of the new updates and features. Even though new tools and new methods are getting discovered, it doesn’t change the fact that Data Science is still growing. We all know that this century is called the “Internet Age” or in other words the “Information Age“. The Internet was first discovered in 1983 by ARPANET. It’s hard to believe how the world change since then. It still makes me feel weird the thing we call Internet, is not even 40 years old. But when we look at the effect it made on us is absolutely measureless.

Computer science was an emerging discipline in the late 1950s that began to consider time-sharing between computer users and, later, the possibility of achieving this over wide area networks. Independently, Paul Baran proposed a distributed network based on data in message blocks in the early 1960s and Donald Davies conceived of packet switching in 1965 at the National Physical Laboratory (NPL) in the UK, which became a testbed for research for two decades.

The importance and the value of data has grown with the beginning of information age. And another factor that increased the data was the amount of users, who were using the internet. In 2016, there were 3.4 billion active internet users, imagine the number these days, where everything is happening over the internet. Here is a nice chart showing the user numbers by years.

Data Science

As the importance and the value of Data increases, scientists started to work on it and with some time, it became a new called Data Science. Can you imagine the amount of data you create every single day, when you are posting a new instagram story, then a post on your blog, then a video you’ve uploaded on YouTube and so on. Now multiply that number with the population of the internet users. Yes, even thinking about the amount of day humanity creates in single day is absolutely excessive. And this doesn’t seems to end anytime soon, so you should at least know what Data Science is and if you think it matches your character, you should consider to become one. If you reading this post, I am sure that you already made your first step into Data Science, so this is great!

Enough with the introduction, let me introduce you to the top five career paths that you should consider:

1- Data Scientist

Discover, clean, and organize valuable information for the organizations. Data Scientists should have the ability to break down and analyze large complex and prepared data to discover new patterns that will profit a company and help them to make better business decisions.

In this career, you will have an experience in a variety of advanced modeling and machine learning techniques: generalized linear models, survival analysis, clustering, time series, tree based algorithms, and neural networks

2- Machine Learning Scientist

Provide technical contributions in a fast-paced team environment to accelerate their efforts on building new analytics. Machine learning scientists often go by titles like Research Scientist or Research Engineer. They also utilize advanced mathematical models, machine learning algorithms, and operations research techniques to deliver insightful recommendations.

In this career, you will also perform one or more of the following core domain skills: machine learning (ML), natural language (NLP), artificial intelligence (AI), texting mining, and statistical analysis methods, such as classification, association rules, sentiment analysis, topic modeling, time-series analysis, statistical inference, and validation methods

3- Machine Learning Engineer

Machine learning engineers create data funnels and deliver software solutions. They typically need strong statistics and programming skills, as well as a knowledge of software engineering. Also, they are responsible for taking theoretical data science models and helping scale them out to production-level models that can handle terabytes of real-time data.

In this career, you will work directly with data science teams in all markets to assist them with their projects and gather new requirements and insights to support the ongoing development. And respond to change, pick up new technologies and adapt to changing requirements.

4- Data Architect

Ensure data solutions are built for performance and design analytics applications for multiple platforms. Data architects are technical experts who adapt data flow management and data storage strategy to a wide range of businesses and solutions. They’re in charge of continually improving the way data is collected and stored.

In this career, you will coordinate with other departments to identify future needs and requirements. And you will optimize new and current database systems.

5- Business Intelligence Developer

BI developers design and develop strategies to assist business users in quickly finding the information they need to make better business decisions. BI developers uses query tools, data visualization and interactive dashboards, and data modeling tools to present their results with the team members.

In this career, you will design and develop enterprise and departmental business intelligence, data warehousing and reporting solutions. Also develop and implement reports and queries to drive business processes.

Thank you for reading this post. Hoping that it gave you some insight about the careers that you can think. We are definitely going through interesting time, and the best way to stay alive to adopt. Data Science is great place field to be working in. But also do it if you are enjoying it, don’t do because of the salary or just because it is a popular field. Your happiness is more important than anything else.

Follow my blog to stay inspired.

Thank you,


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