Who is a Data Scientist - the eyes of the employer
Ksenia Suvorova, director of development for Fontanka.ru , and Andrei Miroshnichenko, coordinator of the offline program “ Data Scientist ”, specifically for the Netology blog, told about the profession of Data Scientist from the employer: what specialists are required by the market, what competencies they are expected from and how they are hired to work.
Now everything has turned out this way, as once the story with product and project management: there are specialists on the market, they already have a fairly well-established market value, there are vacancies, but not everyone knows who this person is and why this person need a business. Therefore, we decided to talk with Avito, the Spice IT HR agency and Storia.me, in order to understand what the development of the profession really is.
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“The need for data science specialists is very high and will only grow in the future. However, there are also many opportunities for learning: anyone who understands that he lacks an academic education can take courses and get the necessary base.
The question is, rather, who and why comes into the profession. At the interview, applicants say that they are interested in machine learning, and when you begin to ask why, they answer: "This is fashionable." And that's all. Understanding how to apply knowledge, no.
And in the business is not so. There is a task for which it is necessary to find the optimal solution method. The specificity is that this solution is practically realizable. And this is probably the main problem that we face in selecting people.
Skills can be divided into hard and soft. As for hard: education is necessarily mathematical. The specialist must understand how mathematical models work.
Basic skills check on the test task. The department is large, it consists of several departments that support different systems. Therefore, each department has developed its own case, as close as possible to what it has to do in the future. When solving such a case, the candidate’s skills become obvious. After that we look at the code and decide who to invite to the meeting.
About soft skills. This is the part that we will definitely pay attention to in person with the candidate. Since data science specialists are involved in cross-functional projects, it is very important for us that a person shares company values, can work in a team and build communication with colleagues. ”
“Data Scientist jobs are becoming more and more. Data is the most valuable product on the market. Recession in the near future will not be. There are not enough specialists, especially if we are talking about such vacancies as Head of Predictive Analytics or Lead / Chief data scientist. Candidates are busy on serious projects and do not want to quit. Plus, these positions imply the presence of special qualities required by a company. It’s easier with interns and junami: data science is gaining momentum, and many are happy to try their hand in this area.
“In Storia, in one period there were two big data specialists. We hired them for specific tasks: it was necessary to work with a predictive analysis in order to improve marketing indicators and correct the situation with a high churn rate. In addition, we wanted to build our own recommendation system inside the site, without taking a ready-made solution for this.
Working with big data can be useful for UX, and for development, and for marketing. It is necessary to look, whether the expert of such format is really necessary.
I would say that the future is really working with big data, but with some reservations. It is not enough to get the data, you also need to understand how to use them. Specialists working with data can be engaged in many tasks, but usually they are nevertheless necessary for a large company - there are tasks and budgets for them.
For large companies in the conditions of stalled growth, a specialist in data science is an opportunity to find a new way of development, a way to attract solvent customers. Working with Big Data is not something that a person can do, because our brains are simply not able to process so much data.
Now only develops an understanding of the necessary competencies and the image of a specialist in working with big data. Too new is the direction for the Russian market and our realities. We have to the rest of the specialists are not always correctly formulated the requirements, what can we say about Data Scientist.
In addition, it must be understood that working with big data only results in the long term and does not solve the issues that need to be resolved today or tomorrow. For example, you are planning to redesign in a year, and you want to make a full-fledged friendly interface. In this case, you hire a specialist for working with big data, he conducts A \ B-tests and predictive analysis. Such data is more accurate because it is machine learning, which does not allow for errors. And it’s also more competent and wide opportunities for advertising campaigns, the target audience and its analysis. ”
Courses "Netology" on the topic:
Now everything has turned out this way, as once the story with product and project management: there are specialists on the market, they already have a fairly well-established market value, there are vacancies, but not everyone knows who this person is and why this person need a business. Therefore, we decided to talk with Avito, the Spice IT HR agency and Storia.me, in order to understand what the development of the profession really is.
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Avito 's perspective from a direct employer position - says Alexander Golovin
“The need for data science specialists is very high and will only grow in the future. However, there are also many opportunities for learning: anyone who understands that he lacks an academic education can take courses and get the necessary base.
The question is, rather, who and why comes into the profession. At the interview, applicants say that they are interested in machine learning, and when you begin to ask why, they answer: "This is fashionable." And that's all. Understanding how to apply knowledge, no.
And in the business is not so. There is a task for which it is necessary to find the optimal solution method. The specificity is that this solution is practically realizable. And this is probably the main problem that we face in selecting people.
Some applicants believe that it is enough to come up with a beautiful algorithm, and the fact that it cannot be applied anywhere is a tenth thing.Examination, in turn, can be divided. There are people who have worked in the field close to us - klassofaydah and IT. They perfectly understand where and how to apply knowledge. People who come from another sphere - from banks, yesterday's graduates or who have worked in the laboratory - in this regard lose, but for us this is not an indicator. They go into deep learning, deep networks, trying to find something more complicated. Although in reality the model that will work can be much simpler.
Skills can be divided into hard and soft. As for hard: education is necessarily mathematical. The specialist must understand how mathematical models work.
They come to us, as a rule, from leading universities: MIPT, HSE, Moscow State University. Among the graduates of the latter, in jest, there is even a competition, of which there are more in the company - graduates of mechmat or VMK.There is also a conditional division into product analysts and ML analysts. The task of the first is to look for an opportunity to improve the product, generating hypotheses about possible problems for users and ways to solve them quickly, and the second automates the solutions found by product analysts and tasks using various ML methods: personal recommendations, pricing, and so on.
Basic skills check on the test task. The department is large, it consists of several departments that support different systems. Therefore, each department has developed its own case, as close as possible to what it has to do in the future. When solving such a case, the candidate’s skills become obvious. After that we look at the code and decide who to invite to the meeting.
About soft skills. This is the part that we will definitely pay attention to in person with the candidate. Since data science specialists are involved in cross-functional projects, it is very important for us that a person shares company values, can work in a team and build communication with colleagues. ”
Spice IT - from the point of view of HR agency
“Data Scientist jobs are becoming more and more. Data is the most valuable product on the market. Recession in the near future will not be. There are not enough specialists, especially if we are talking about such vacancies as Head of Predictive Analytics or Lead / Chief data scientist. Candidates are busy on serious projects and do not want to quit. Plus, these positions imply the presence of special qualities required by a company. It’s easier with interns and junami: data science is gaining momentum, and many are happy to try their hand in this area.
Professional competencies depend on the requirements of the client company. From the main one can be distinguished: R, Python, Machine Learning, databases, such as MSSQL, MySQL, Postgresql. Candidates for the position of Data Scientists should be well versed in mathematics, statistics and programming.Jobs, where soft skills are one of the key requirements, are quite rare, unless it is a leadership position. Due to the fact that there are not so many strong specialists in the market, the emphasis is on the technical component.
Of course, many companies would like to see in their ranks specialists with a proactive attitude, prepare presentations, make up beautiful reports and know how to establish contact with colleagues and management, but again, in practice, most customers rely on these requirements, preferring to communicate sociability with good technical experience.At the same time, companies are ready to train, accepting candidates as interns or junior analysts. Ready to watch the guys who lead projects on freelancing or doing something for themselves in order to gain experience. We have jobs at various levels, where we need specialists with minimal experience or a strong technical background. There are lots of options, everyone can pick something up.
Experience with Data Scientist ex-marketing director of Storia.me - Alina Gashinskaya
“In Storia, in one period there were two big data specialists. We hired them for specific tasks: it was necessary to work with a predictive analysis in order to improve marketing indicators and correct the situation with a high churn rate. In addition, we wanted to build our own recommendation system inside the site, without taking a ready-made solution for this.
It seems to me that Data Scientist should be able to work under the tasks of the product, but without basic skills, of course, nowhere. Languages for data collection, queries, information processing, work with databases, certain knowledge in statistics - this output pool will be used for a specific task, and in any situation Data Scientist must understand how it will solve a particular problem.It does not make sense to hire a specialist for working with big data so that he just sits in the office - it will be quite expensive. It is more profitable to hire a project if there is no third-party solution or if the product needs internal development.
Working with big data can be useful for UX, and for development, and for marketing. It is necessary to look, whether the expert of such format is really necessary.
I would say that the future is really working with big data, but with some reservations. It is not enough to get the data, you also need to understand how to use them. Specialists working with data can be engaged in many tasks, but usually they are nevertheless necessary for a large company - there are tasks and budgets for them.
For large companies in the conditions of stalled growth, a specialist in data science is an opportunity to find a new way of development, a way to attract solvent customers. Working with Big Data is not something that a person can do, because our brains are simply not able to process so much data.
Now only develops an understanding of the necessary competencies and the image of a specialist in working with big data. Too new is the direction for the Russian market and our realities. We have to the rest of the specialists are not always correctly formulated the requirements, what can we say about Data Scientist.
In addition, it must be understood that working with big data only results in the long term and does not solve the issues that need to be resolved today or tomorrow. For example, you are planning to redesign in a year, and you want to make a full-fledged friendly interface. In this case, you hire a specialist for working with big data, he conducts A \ B-tests and predictive analysis. Such data is more accurate because it is machine learning, which does not allow for errors. And it’s also more competent and wide opportunities for advertising campaigns, the target audience and its analysis. ”
Tips an employer can give to a big data specialist
- Courses, of course, needed. But they must be built up on the knowledge of programming languages: R or Python.
- Without understanding the principles of machine learning - nowhere.
- Math and statistics should be your friends.
- Data is numbers, numbers, mathematical analysis. So make them your gods.
- It is not enough to know the theory, it is necessary to understand the practical component. To go to work in a business and think that an angel horn of data is needed there is a mistake. There is a need to solve a specific problem.
- In Russia, big data is, above all, an analyst. Therefore, if you want to do something else, then you will have to look for a job longer.
- You may get a "hard" employer who himself will poorly understand the role of Data Science - this is normal. You are not a marketer, not a traffic manager, or even an analyst, you are something more.
- The task of any Data Scientist is to process the data and provide the result. With the help of your knowledge and skills, drones fly around the world, taxis and cars without human control will soon fly, neural networks operate, millions of advertising campaigns are processed in Google and Yandex. You are priceless, but everything has its price and its name is salary. Appreciate yourself and success to you.
Read the full interview with Avito and Spice IT about Data Scientist specialists in our next article .
From the Editor
Courses "Netology" on the topic:
- full-time course " Data Scientist ";
- online program " Big Data: Basics of working with large data arrays. "
Source: https://habr.com/ru/post/346806/
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