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recruter des data scientists

    What are data scientists looking for?

    First of all, the role of data scientists is to deliver data-intensive applications as seamlessly as possible. As a result, the three key skills in data science are computing, algorithms and business. Data scientists therefore have essentially technical profiles and a very advanced level of expertise. When working on a project, you need to work with a number of people, so you need to find those who not only have new and innovative ideas to contribute, but who also have good interpersonal skills.


    It’s important to remember that these profiles are hard to find, but a large community has developed around Data Science. They meet up at Meetup events, organise conferences and pass on their knowledge. They also have the opportunity to train on platforms such as Coursera, to acquire additional skills. There are also challenges in which they can compete in teams.


    The aim of data scientists is to provide concrete answers to problems, so that decisions can be taken. It should be noted that they also seek to provide innovative approaches using appropriate technologies. Finally, as we have seen, they generally have a sense of belonging to a community: they show a willingness to exchange with others, to share and to learn.


    The keys to attracting them

    The first thing to consider is the company’s culture and identity. Data scientists will be interested in companies that value analytical approaches and that aim to constantly improve their offering by processing data. It is therefore in the company’s interest to encourage this type of approach by providing easy access to the company’s data, so that everyone can find something to develop analytical approaches.


    When we talk about Data Science, we also take into account the spirit in which the approaches are developed. As this is a field that has evolved very recently as a result of market needs, it is important to bear in mind that Data Scientists have an innovative and modern mindset. For example, this idea can be found in start-ups: you define an objective, envisage several possibilities for achieving it, test them and accept failure in order to bounce back.


    On the other hand, it’s important to help them project what is expected of them in the company. This gives them a very clear idea of the strategic challenges and initiatives that will be taken within the company.


    Last but not least, Data Science candidates attach a great deal of importance to the technical environment. It’s not just a question of presenting an ambitious project, but above all of having the technological and IT capabilities! So you need to be open to the introduction and use of new technologies.


    How should the recruitment process be organised?

    The main objective is to ensure a relevant selection of candidates so as to reach the best people. You therefore need to select the media through which you advertise your vacancies, based on their relevance to this community. For example, there are recruitment forums specialising in Data Science and challenges organised on Job Boards, so these are worth keeping an eye on. It should also be noted that Data Scientists are highly connected, so the vast majority of them are on social networks. Relaying job offers for Data Scientists on these networks is therefore an excellent way of attracting them.


    Once this first stage has been completed, the candidates still need to be sorted. To assess the different types of application, it is a good idea to offer candidates a hands-on technical test, i.e. they are asked to analyse a set of data using the language of their choice. We can also ask candidates to brainstorm with us on a data-related issue facing the company, to highlight their ideas and their ability to think on their feet. You can also ask them to meet the various people involved in the Data project, to check that they are able to communicate well with them.


    Any advice?

    Adison.ai is involved firstly in creating and advertising the job vacancy, and then in selecting the best candidates. Using social networks, we can help you acquire the best Data Science talent, according to your criteria and expectations. Contact us to find out more!

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