Data Scientist Job and Role Description
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All the keys to understanding the profession of Data Scientist. In this article, we will know more about the Data Scientist Job and Role Description
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Data Scientist Job and Role Description
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Data Scientist is responsible for big data management and analysis. More than that, it is in charge of the recovery and processing of millions of information because beyond the function of the “Data Analyst”, the Data Scientist has the role of making the data speak and putting it at the service of the management of a company. This business is both functional and strategic.
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Although this is a recent occupation, Data Scientists are found in many industries. Finance, IT, insurance, e-commerce or retail; so many areas in which data scientist can practice. Indeed, his various technical skills allow him to adapt to his work environment. But it is his little-known expertise that makes his profile very attractive to recruiters. This is why these rare profiles are highly sought after. In fact, some companies choose to combine different profiles to create a Big Data team because of the technical complexity of the tasks requested for this position.
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First of all, it is important to note that Data Scientist’s business appears in an environment of increased market competition. It asks decision-makers to support their decision-making on reliable statistics.
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In addition, the fields of analysis of data in companies are very broad: production data, market analysis and predictions, knowledge of customer behaviour, marketing accuracy, company results… Thus, data scientist plays a big role in creating valuable indicators at all levels of the company. It is thanks to the precision of his analysis that he can develop prediction models. It can be said that he is committed to improving the overall business.
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Also, although the Data Scientist’s missions differ from the Data miner, some consider it to be the evolution of the latter’s position.
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Data Scientist’s Main Responsibilities
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Study of data in the company’s possession that will define the data that will be extracted and processed, in accordance with management’s requirements,
Recovering and analyzing relevant data related to the company’s production process, sales or customer data,
Building algorithms to improve search and targeting results,
Developing predictive models to anticipate changes in business activity data and trends,
Modelling data analysis results to make them readable and usable by managers,
Business recommendations to the general management to improve decision-making. This data interpretation work can also be done through the creation of a specific dashboard and/or custom software that analyzes the data processed. The creation of decision support metrics can have a significant impact on the company’s strategy.
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Related missions
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Defining data storage solutions, in conjunction with the information systems management,
Participate in the recruitment of big data experts to complement the team working on data processing,
Research and development related to the processing of large volumes of data.
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Data Scientist Career Progression
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The next step for a Data Scientist is to be a Chief Data Scientist.
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What is the role of Chief Data Scientist?
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As for the Chief Data Scientist, he manages a team of Data Scientists. He is responsible for data analysis projects but also for the implementation of measurement tools. He is directly involved in the company’s strategy and participates in the decision-making process.
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Profile
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The Chief Data Scientist is coming out of a higher education in engineering school, computer science or statistics school. It also warrants 4 to 5 years of experience in data analytics (Data Analyst or similar) or in a data centre environment (in contact with large data structures). Currently, there are very few specialized training courses on this trade.
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Skills
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Strong computer programming skills (Java, C-) and a good understanding of data structures,
Expertise in algorithm and database management (NoSQL, Cassandra…),
Mastery of the architecture of decision-making databases (data warehouse),
Applied Mathematics: Building algorithms to improve search and targeting results,
Statistics: ability to perform predictive and statistical analyses from different databases,
Project management skills will also be appreciated.
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Salary of a Data Scientist
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His remuneration depends largely on his experience but also on his ability to develop powerful and effective algorithms. However, its expertise is recognized only when it is able to produce accurate and decision-making data models.
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