A data scientist (aka Data Science specialist) can find a job in any field: from retail to astrophysics. Because he is the real master of big data. Everyone who comes to Data Science can be divided into four streams. There are those who become data scientists after professional education, but such courses are still few in universities. There are also people of technical and scientific professions who want to find more promising work with a large salary. The third stream consists of developers who get tired of boring programming and are looking for interesting tasks.


What does a data scientist do? Business Model Generation
What does a data scientist do, how much does he earn and is it really the sexiest profession?

Data Scientist applies Data Science methods to process large amounts of information. He builds and tests mathematical models of data behavior. This helps to find patterns in them or to predict future values. For example, based on past demand data, a data scientist can help a company predict next year's sales. Models are built using machine learning algorithms, and databases are operated using SQL.

What tasks does Data Scientist solve?

Jobs in Data Science imply working in wherever there is a large amount of information: most often they are large businesses, startups and scientific organizations. Since the methods of working with data are universal, all areas are open to specialists: from retail and banks to meteorology and chemistry. In science, they help make important discoveries: they conduct complex research, for example, build and train neural networks for molecular biology, study gamma rays, or analyze DNA.

In large companies, the data scientist is the person that all departments need.

In startups, they help develop technologies that take the product to the next level: TikTok uses machine learning to recommend content, and MSQRD, which Facebook bought, uses face recognition technology and artificial intelligence.

What does he need to know?

Data scientist job requires you to know mathematics well: linear algebra, probability theory, statistics, mathematical analysis. Mathematical models allow you to find patterns in the data and predict their values ​​in the future. And in order to apply these models in practice, you need to program in Python, be able to work with SQL and libraries (a set of ready-made functions, objects and subroutines) and frameworks (software that combines ready-made components of a large software project) for machine learning (for example, NumPy and Scikit- learn). For more complex tasks, data scientists need C or C ++.

The results of data analysis must be able to visualize, for example, using the Seaborn, Plotly or Matplotlib libraries.

What does his working day look like?

Whether a data scientist needs to work in an office depends on the company. You can find about 10% of vacancies for remote work. Sometimes companies offer to combine work from the office and from home. Interaction with the team depends on the scale of the tasks: a newbie preparing data for processing can only communicate with a manager, and a data scientist signor must communicate with customers and delegate tasks to the team.

As a rule, the working day begins with sorting mail and communicating with the team. Then work with the data begins: you need to write SQL queries and prepare arrays of information for machine learning, write model code in Python and run the data through the model. In the process of work, you need to periodically call up with the team and managers who will use the model in practice.

There are specialists who started from scratch: if newbies have self-discipline and an interest in big data, then they become good data scientists. Finally, there are those to whom Data Science comes on its own, for example, to bioinformatics.

Is there demand in Data Scientists?

In large companies, they only talk about data science jobs. According to the World Economic Forum, work in Data Science ranks first in the ranking of professions with the highest demand in the market until 2025.

Data Science is one of the fastest growing professions in IT, and companies are in short supply of specialists. Over the past three years, the number of vacancies has grown by 433%.

How to become a Data Science Specialist?

Now is a good time to enter the profession - the competition is still low. You can master it even with zero knowledge: the main thing is to be interested in big data and be ready to study and work a lot.

You can take free courses (here's a selection of open online Data Science courses from Harvard University), and then compete in Kaggle events such as AI Journey. Not all companies need to know everything perfectly, but with a good understanding of mathematics, knowledge of the programming language and machine learning, you can apply for an internship or junior position.