The profession of Data Scientist consists in processing and enhancing data, which is now mass produced in the era of Big Data. This professional is a manager responsible for setting up a coherent data exploitation strategy for the company that employs him.
The Characteristics Of The Data Scientist
The Data Scientist deals with the management of incoming information with a view to using it for commercial purposes. Being required to handle very large amounts of data and to be in contact with figures, he must have excellent analytical skills. His interpersonal and communication skills are essential qualities expected for this type of position. The Data Scientist must discuss with the technical and functional teams in order to assimilate and better understand the data and the problem to be solved. Force of proposal, he must be constantly on the lookout for new information relating to his trade and seek to broaden his field of action.
The Main Missions Of The Data Scientist
Understand And Define The Business Case
The prerequisite before getting down to work is to identify the needs and fully understand the market issues. Also, the Data Scientist seeks to fully understand the environment in which the company operates. He collects a large amount of data which he transforms into mathematical and statistical problems.
Eg: competition is increasing in the market for telephone packages. How to prevent current customers from leaving?
Collect And Organize Data
Very often, the necessary data is dispersed in several databases of the company’s information system. To exploit them, the Data Scientist relies on his technical knowledge. It extracts data , cleans it (data cleaning) and organizes it.
Ex: the data is distributed in the customer information system, the contract monitoring system and the accounting system. This data must be organized into a single database that makes it possible to identify which customer left and what their characteristics were.
When the data is organized, the data scientist begins by analyzing it. What is the distribution of each variable? Are there any abnormal points? Are there any missing data? How to deal with these problems? It is essential to ensure the quality and relevance of the data used. False data will give erroneous analyses.
Ex: the data contains customers over 150 years old, missing data on the type of plan purchased, etc.
Once the data has been validated, the data scientist uses it to examine a number of more or less complex questions. His knowledge of Data Mining , Data Visualization and statistics are therefore essential.
Eg: do customers of the À package leave more because they are younger or because they have less seniority?
Predict From Data
In most cases, Data Scientists then use the data to predict, using artificial intelligence algorithms, either Machine Learning or Deep Learning.
Data Scientist Tools
To do their job, the Data Scientist uses various data transformation, analysis and modeling tools. As shown in the video below based on a large community of data scientists, open source Python and R solutions are enjoying increasing success. Python is very functional and has a growing community of users, but R has a large community of researchers and has unique statistical tools.
Setting Up A Strategy
Then, he meticulously analyzes this data in order to put in place a good organizational and operational strategy for the company. At the end of this, he draws marketing and commercial solutions allowing to build customer loyalty or enhance the brand image. The sources exploitable by the Data Scientist are numerous and dispersed on various networks. The latter takes steps to group them, study them and then synthesize them.
But What Does A Data Scientist Do On A Typical Day?
For those interested, see also the daily life and career of a data scientist. This gives a more concrete idea of the reality of this profession for those who seek to hold this job.
Also Read: Know The Basics Of Business Development