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The profession of Data Scientist – a specialist in processing, analyzing and storing large amounts of Big Data – in the modern world is considered one of the most promising, relevant and highly paid.
The demand for these specialists is growing rapidly from year to year. With the current trend of Big Data growth in all industries, the need to train managers in the basic skills of working with big data arrays is growing. That is why the faculties of the most prestigious universities for training data specialists are so rapidly and widely funded. You can also acquire the most in-demand skills with Data Science Course online if you want to start your career in data science.
What is data science?
Data Science, that is, the science of working with data, is not just a new buzzword in the IT world. This is what will change the world of programming, business, and even consumers, just as much as the invention of the steam engine and the personal computer did. In fact, Data Science is already changing it, as evidenced by many startups in the field of big data and artificial intelligence.
Data scientist role
In fact, there are a lot of myths about this profession. In the eyes of some, Data Scientists are like shamans who are able to extract oil from “big data”, and they do not need business knowledge from them. Many people think that if you know how to program, than you understand what to do with data.
What do data scientists do? Such professionals are divided into three skill groups:
- IT literacy with all the necessary skills;
- Mathematical and statistical knowledge;
- Substantial experience in a certain area – understanding the business needs of your organization or the tasks of your branch of science.
Moreover, data scientist job description that imply this specialization can be called differently. And the requested skills are also rather numerous.
Data scientist responsibilities
What is a data scientist? Features of the Data Scientist profession:
- the ability to get the necessary information up to the request;
- to establish hidden patterns in data sets;
- statistically analyze them to make smart business decisions.
The workplace is presented as a set of servers.
At the moment, specialists of this level are sorely lacking. The demand for Data Scientist is only 30% satisfied. More details about it are here https://blog.dataart.com/taxonomy-of-data-professionals-find-the-right-one-for-your-business.
Specifical tasks for data scientist
When hiring, a Data Scientist is primarily assessed for his ability to immerse himself in a problem and strive to solve it in any way. To do this, the candidate for the position is offered a test taken out of context. A real scientist, without unnecessary clarifying questions, will completely immerse himself in the task, examining it from different sides, from different angles, creating various probabilistic models with random variables, trying to identify a pattern. This is the manifestation of non-standard thinking and persistence in the search for a way and tools to solve the problem.
Such problems can be avoided with a good understanding of the mathematical foundations of these methods. Also there should be good knowledge of the theoretical basics.
Job titles for data scientist
The main ones that can most often be found among job vacancies are:
1. Data architect. Data architecture is the set of rules for definition of the type of information and its use.
2. Data engineer. The knowledge of machine learning and statistics is not required for a data engineer, but it is a very important person on any team.
3. Data analyst. This role is less technical than the data scientist, although in many ways they are similar and often confused.
There are many peculiarities in data analyst vs data scientist vs data engineer, which are important.
Salaries
Such specialists are in great demand nowadays. An undersaturated market cannot provide companies with qualified personnel in the field of Data Mining or predictive analytics, which leads to an increase in demand and wages. Salaries start at $ 800.
You may also like: The Demand for Data Scientists
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