For example, we use autocorrection run by AI and have a lot of custom recommendations presented to us via e-mails or commercials on platforms like YouTube, Facebook, et cetera. But the truth is that data scientists do so much more than “simply” managing Artificial Intelligence. Today we will explore the data science world.
What does a data scientist do?
First of all, why do we even need a data scientist in our company? Well, companies reach out to a data scien-tist with the most complex and difficult problems and ask them for directions (https://addepto.com/data-science-consulting/). The world has changed due to the usage of the internet on a large scale. We have to take into consideration not only our neighborhood, but we must think globally about our businesses. The vast amount of data, which is called Big Data, is hard to analyze but it contains a lot of useful knowledge, for ex-ample about what our customers want and need. Therefore, it is really important to be aware of that, so we can implement it and increase our income and customer satisfaction at the same time.
Before AI (Artificial Intelligence) is modeled by the data scientist, there are other things to focus on. Firstly, data scientist gathers data about the company from many different sources, then organizes, cleans and ana-lyzes data by various methods, algorithms and processes to find patterns which can help solve the problem or show opportunities to bring the company to the next level. The data scientist must also be good at communi-cation and visualization, so they could present those solutions to stakeholders.
Data scientist’s work is a significantly individualized one. It requires hours of sitting alone with sheets of data and solving puzzles. Accuracy and a sharp mind are essential in this work. Almost half of the data scientists have PhDs.
Artificial Intelligence in data science
The final solution in the form of AI is the last stage of data scientist’s work. Firstly, the AI modeling occurs which means that data scientists create and test different machine learning algorithms to make sure that the final product of their work is ideally suited to the needs of the company. After this stage data scientist builds an application run by the machine learning Artificial Intelligence.
What fields can benefit from data science?
The first thing that comes to mind is, of course, the retail sector, but AI helps analyze data in many different fields of business. For example, healthcare, gaming, e-commerce, marketing, financial services and more. Wherever there is data, there is a need for data science.
