Now everyone around is talking about how important it is to collect data, analyze it and use it to improve customer service, optimize business processes and increase profits. All of this is done by Data Scientist.


Who is Data Scientist International business: competing in the global marketplace
According to LinkedIn statistics, 831,000 such specialists have been hired worldwide since 2018.

Data Science jobs and activity of such a specialist is not scientific, but practical: he works with company data, analyzes them, looks for dependencies, draws conclusions based on them and, if necessary, builds visualizations. To do this, Data Scientist uses different mathematical algorithms, special software and development tools.

Of the more familiar specialties, Data Scientist is closest to the programmer and business analyst.
The data with which Data Scientist works can be any: sound, text, photo, video, tables, documents. If you have any data and need to analyze it - this is the job for the Data Scientist.

Other specialists work in the data field, for example, Machine Learning Engineer, Data Engineer or Data Analyst. They have a narrower specialization, for example, Machine Learning Engineer is less engaged in data analysis, mainly develops machine learning models. Data Scientist is a broader term that refers to a person with different competencies in the field of data analysis.

Companies usually hire one Data Scientist at the start. In the future, if there are too many diverse tasks related to data, you can hire several such specialists, that is, create an entire Data Science department.

What Data Scientist does

Often times in business there are tasks that are solved manually. For example, a manager makes simple calculations in Excel, or a store manager predicts the demand for goods from his own experience. These manual decisions are time consuming and often biased.

jobs in Data Science are connected to automation of these decisions and makes them more accurate, data-driven. He understands the problem, looks at what data is needed to solve it. Then he develops a program that will automatically read and analyze the data. Such a program can either make simple decisions on its own, or provide more accurate and useful information to managers.

Data Scientist often solves common tasks typical for any business: analyze customer behavior, attract and retain a customer, predict demand, build a recommendation system, and launch an effective campaign. But there are also specific tasks: the bank wants to predict the likelihood of loan repayment, the call center wants to automate answers to frequently asked questions. Data Scientist helps with this too. It also happens that Data Scientist does not solve a specific problem, but analyzes the current situation and looks for growth areas for the company.

Data Scientist tasks are almost always related to machine learning. This happens because it is machine learning and artificial intelligence that are well suited for automating business processes.
Data Scientist does very different things in different companies. But in the end, they do one thing: help you save money, increase income, or make the right decision.

If a company is technology-related, such as developing artificial intelligence or automation tools, it needs Data Scientist right from the start.

If the company is not directly related to IT, Data Scientist usually becomes necessary when there is a lot of data and business processes, it is difficult to manage them manually. This usually happens in large companies that have already tried different ways to increase profits and have come to the conclusion that it is necessary to extract new information from the collected data, automate certain processes and look for other approaches to working with clients.

“If the business is already digitalized, Data Scientist is definitely needed at least to put things in order in IT systems and search for insights to generate additional profit. If the business is not digitalized, Data Scientist will also come in handy to predict something, analyze competitors, or suggest how to approach the issue of digitalization. For example, imagine an agricultural firm that grows food. Data Scientist can help her predict soil moisture in her fields and chart her irrigation schedule. ”

What a Data Scientist needs to work

The main thing Data Scientist works with is data. The company must already collect, process and store data, build the appropriate infrastructure for this.

Wikipedia deals with processing data, which often requires a lot of computing power and special tools.

Data Scientist also needs a team of assistants to work. Most often, he works in conjunction with the Data Engineer and the development team. The former provide it with data, the latter turn the developed models into specific programs and services that other people can use.