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Data & Business Intelligence Job Descriptions

Data Scientist: Job Description

Data Scientist Job
A Data Scientist is an expert in Data Science, whose job is to extract knowledge from data in order to be able to answer the questions he or she is asked.

Use our template to create a compelling and comprehensive Data Scientist job description to attract top talent.

A Data Scientist is an expert in Data Science, whose job is to extract knowledge from data in order to be able to answer the questions he or she is asked.

In this article you will find all you need to know about the job of Data Scientist, the skilled required, education and training, and the salary expectations.

Also discover what are the differences between Big Data and Business Intelligence

Data Scientist: the job

For the past few years, the job of data scientist has become increasingly relevant due to the growing popularity of Big Data. It is one of the most promising career paths in the IT sector.

Nature of the work

The Data Scientist’s job is based on 4 main missions:

  • Identify the needs and problems that the company entrusts to him/her (several possible areas: marketing, HR, customer loyalty, etc.)
  • Define a statistical model that will enable him/her to respond
  • Build the appropriate tools to collect the data
  • Collect and organize the data to exploit the results. The data can come from various sources.

Required skills of the Data Scientist

Ability to analyse and synthesise

The Data Scientist must be able to anticipate information needs and constantly seek new sources of information.

Technical skills

The mastery of certain technical skills is essential for the Data Scientist. Indeed, they must master NoSQL databases (MongoDB, Hadoop), R programming language, C programming with the Python language…They must also have a solid foundation in statistics as well as notions of machine learning, which can be a real asset.

Curiosity and open-mindedness

To work in this profession, you must also be able to detect the most interesting data. In addition, a passion for information processing and Big Data issues is obviously a plus.

Context

Two engineers from Facebook first used this term in 2008. Harvard Business Review voted Data Scientist as the “sexiest job of the 21st century”. As a result, in large companies, the job is divided into several sub-categories: the data miner (collects data), the data analyst (administers and creates databases), and the data scientist (interprets the data).

Thus, data scientists can be found in different fields, such as the commercial sector or security.

Salary

Depending on the company, Data Scientists work in several areas such as marketing, information systems or the finance department.

Their salary varies between 500 and 800 euros.

Data Scientist: Training and Education

In conclusion, to embark on a career as a data scientist, you need a minimum of 5 years of higher education, with a master’s degree in statistical analysis or computer programming. Many also have a doctorate (bac +8)

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Categories
Data & Business Intelligence Job Descriptions

Data Analyst

The Big Data engineer job cdescription
The Big Data engineer job consist of developing, maintaining, testing, and evaluating Big Data solutions.

Data Analyst is the go-to expert for all operations related to the company’s databases. They assemble and processes data in order to assess business activity and make appropriate recommendations. Their job allows them to “make the data speak” by interpreting them.

This relatively new digital profession is essential in all sectors: commerce, finance, banking, insurance…

Also explore the role of the IoT Consultant

What is the role of a Data Analyst?

Create and model databases

Certainly, one of the first missions of the Data Analyst is to collect, process and study statistical data to produce business analysis and provide recommendations. That is to say, the analyst creates and models the various databases necessary to accomplish the tasks, ensuring proper functioning and the regular updating of the database.

Define segmentation criteria

The Data Analyst is also responsible for defining segmentation. To do this, they must find relevant data sources that allow them, for example, to define the target of marketing campaigns or identify consumer trends.

Popularize data and make it accessible

For example, extracting and translating business data into statistical data makes it possible to synthesize and popularize information. This data processing allows company managers and teams to analyze the data and use it to improve performance.

Required skills of the Data Analyst

An appetite for numbers

Above all, to be a successful, you must first of all love statistics. Reports, tables, graphs… are the main working tools of the Data Analyst.

Knowledge in data analysis and statistical methodologies

An expert in Data Analysis musts also have mastery of statistical methodologies and associated mathematical models to set up efficient analysis systems.

Proficiency in IT tools, languages ​​and databases

Then, Proficiency in the DB SQL computer language, as well as in web analytics tools and data mining tools is often essential for data analysts.

Extreme rigour

Moreover, as this is an activity requiring the manipulation of encrypted data, the Data Analyst must be endowed with extreme rigour, having developed and analytical mind and fool-proof organization skills. Concentration is also one of the skills needed to be a good analyst. They also must keep abreast of new legal and regulatory regulations for data management.

Also read the differences between Big Data and Business Intelligence

Within the industry

The Data Analyst is a more than buoyant function which is set to keep developing strongly. With the evolution of the IT landscape, companies face exponential growth in the number of data. Therefore, large companies in areas like finance, e-commerce, marketing, industry and medicine are the most likely businesses to recruit in this area.

Salary of the Data Analyst

The average daily rate is between €400 and €800.

Training of the Data Analyst

In conclusion, to become a Data Analyst, college-level training is required. Companies tend to favour candidates who have followed courses in engineering, statistics, or even computer science.

To go higher up in this function then, it is recommended to pursue a specialized master’s program. Several career paths are possible, including as consultant positions such as Data Scientist, Business Intelligence Engineer, Data Engineer or even Chief Data Officer.