Data science: The challenges of a multitasking job

The Data Science specialist must know how to navigate skillfully between many languages, think algorithmically, and have the ability to solve complex problems.

These faculties are critical because the data scientist must be able to understand the complexity of data and their flow. A lucidity with regard to the connections between these different elements is indispensable. 

Finally, it is essential for a data scientist to be a tactical consultant for the company. 

The data scientist works close to the data, and can therefore learn more from this data than anyone else. It is therefore incumbent on him to translate his observations and share his knowledge to help solve the company's problems. He must know how to handle the data to narrate a coherent history by using insights like a landing. This business relevance is as important as the mastery of technology and algorithms. The objectives of the company must be aligned with the data science projects. Concretely, the value of a data scientist does not come only from his mastery of mathematics, data and technology, but from a combination of the three. For all businesses that want to use data to drive business growth, data science is the key. Data science projects can generate significant returns on investments. However, recruiting people with the necessary skills is not an easy task. Once a talented data scientist is hired, it is necessary to keep him motivated by providing him with the necessary autonomy and by offering him challenges that match his skills.

Learning the Data Science requires a reward up to the tasks required. This is why data scientists are paid between 40,000 and 60,000 euros a year in Europe. In the United States, this salary can climb up to $ 150,000 a year depending on the data science requirement.

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Certificat de spécialisation Analyste de données massives à l'ISSAE Cnam Liban

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