Data scientist jobs for beginners

Many beginners ask what they need to know and be able to get their first job as a programmer. So, in this article, we will discuss the requirements for the Data Scientist jobs.

Who is a Data Scientist?

The ability to work with Big Data technologies is a rare and valuable skill that opens up the prospect of becoming a super-demanded and highly paid specialist for you.

Data Scientists are people who are engaged in big data: they find patterns and draw conclusions that are useful for their company.

There are several types of Data Science vacancies in the job market. These “types” have a gradation on the level of experience – of course, these boundaries are very blurred and are generalizations, but for convenience, we will choose these three. In ascending order, these are entry-level, junior and senior.

Entry-level or novice date Scientist is a newcomer to the industry. This person does not have a clear idea of the work of the data expert, at least in terms of this workflow. A typical novice Data Scientist is a person who has just received his degree and is now trying to find a job in this now popular field. Some novice professionals already have experience working for the company, but this is a very rare case.

Requirements to the  Data Scientists

Here’s a list of the skills and knowledge that any Data Scientist needs to get started:

  • Mathematical logic, linear algebra and higher mathematics. Without this, it will not be possible to build a model, find patterns, or predict something new.
  • Knowledge of machine learning. The job of a data scientist is to analyze data of huge size, and it is impossible to do it manually.
  • Programming in Python and R. Python is an ideal language for machine learning and neural networks.
  • Ability to receive and visualize data. Not all data scientists are so lucky that they immediately receive ready-made datasets for processing.

What does Data Scientist do? 

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.

In large companies, a Data Scientist is a person that all departments need:

  • help marketers analyze loyalty card data and understand which customer groups what to advertise;
  • for logisticians, it will study data from GPS trackers and optimize the transportation route;
  • It will help the HR department to predict which of the employees will quit soon by analyzing their activity during the working day;
  • with salespeople will forecast the demand for the product, taking into account the seasonality
  • will help lawyers to recognize what is written on documents using optical character recognition technologies;
  • in production will predict equipment based on data from sensors.