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The "Data Scientist" is the Big Data specialist in companies, responsible for structuring information and optimizing the security of stored data, regardless of their volume. Their mission: carefully categorize data to avoid risks of IT system failure. They thus seek to detect new vulnerabilities potentially exploitable by hackers and their impact on company activities. Ultimately, they ensure to propose effective protection solutions. This expert in massive data management and analysis is simultaneously a specialist in numbers, statistics, and computer programs: they extract value from data to support the company in making strategic or operational decisions. The "Data Scientist" collaborates transversally with various profiles: computer scientists, statisticians, data analysts, data miners, marketing and web marketing experts...

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Job VacancyData Engineer Expérimenté(e) F/H - CENISIS

La French Tech
Published on
Data Engineering
Data Lake
Data Warehouse

Lille, Hauts-de-France
Rejoignez une entreprise lauréate ou membre du réseau La French Tech, qui rassemble les start-up et scale-up les plus innovantes de France et contribue à la création de plus de 1,1 million d'emplois directs et indirects en France et à l'international. CENISIS recrute un Data Engineer Expérimenté(e) F/H, en CDI, à Lille, pour intervenir au sein d'une équipe métier chez un grand acteur du Retail. Tes missions : En tant que Data Engineer Expérimenté(e) F/H, tu seras responsable de la conception et de l'industrialisation des flux de données afin de garantir leur fiabilité, leur performance et leur exploitabilité pour les usages métiers et analytiques. Tes principales responsabilités : Concevoir, développer et maintenir des pipelines de données robustes et scalables. Collecter, intégrer et transformer des données structurées et non structurées. Modéliser les données dans des environnements Data Warehouse / Data Lake. Optimiser la performance, la qualité et la disponibilité des flux de données. Automatiser les traitements et les déploiements dans une logique DataOps. Collaborer avec les Data Analysts, Data Scientists et équipes métiers. Garantir la fiabilité et la sécurité des données mises à disposition. Participer à la veille technologique sur les environnements data et IA. En rejoignant CENISIS, tu bénéficies notamment : Prise en charge à 100 % des transports en commun ou indemnités kilométriques vélo. Charte télétravail co-signée par la direction. Prime de performance. Et évidemment, les avantages classiques : Tickets restaurant. Mutuelle d'entreprise. Le processus de recrutement : Chez Cenisis, le processus de recrutement s'adapte au contexte des missions et peut être accéléré en fonction des besoins : Première rencontre avec Alexandre, Talent Acquisition, Deuxième échange avec ton futur Manager, Troisième échange avec Gilles, Head of et/ou Cédric, CEO.
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Job VacancyLead Data Engineer

█ █ █ ██ █ █
Published on
Apache Kafka
Apache Spark
Big Data

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Frequently asked questions about working as a Data Scientist

What is the role of a Data Scientist

In the Big Data era, the Data Scientist is somewhat the evolution of the Data Analyst. He/she is a specialist in analyzing and exploiting data within a company. His/her role is to give meaning to this data, in order to extract value from it, to enable the company to make strategic and/or operational decisions. It is one of the high-responsibility positions in a company.

How much does a Data Scientist charge

The average daily rate of a freelance data scientist is around £450/day. It can vary depending on years of experience and the professional's geographical location. The salary of a junior data analyst is £35K. The salary of an experienced data scientist ranges from £50K to £60K.

What is the definition of a Data Scientist

The Data Scientist is an essential element of the company, given that they are responsible for analyzing massive data called Big Data. They manage the collection, storage, analysis and use of millions of data points collected through different channels. This data is used to analyze company performance, and to anticipate consumer behaviors or new trends. It's both an exciting and promising field. It generates new challenges and allows professionals to continuously gain skills. The Data Scientist has solid knowledge in marketing. This professional is highly sought after by companies that constantly seek to improve their performance and remain competitive. After completing their analysis, the Data Scientist will then write a report explaining their conclusions to management or their client.

What type of mission can a Data Scientist handle

The Data Scientist's main mission is to "predict the future". The significant amount of data that companies now generate can be very useful if used properly. The data scientist can then ensure the strategic development of the company, as well as its digital transformation. To achieve this, they must decipher opaque masses of data to give them meaning. Their role is therefore to transform data into actionable information. They can offer their clients IT management solutions to meet specific needs. Creating algorithms will allow them to anticipate future behaviors and needs in order to guide important decisions. It is this form of creativity that distinguishes them from the Data Analyst. Thanks to their expertise, the Data Scientist must be able to present innovative and relevant proposals to their clients, implement and deploy machine learning models, and finally communicate their conclusions to the relevant departments. They can work on short or medium-term projects.

What are the main skills of a Data Scientist

The Data Scientist must master many skills to effectively carry out their duties. We can mention a few: • Being able to efficiently analyze statistical data and model it • Having good knowledge of programming tools and computer language • Mastering data visualization techniques • Having strong affinities for marketing • Having business sense and good communication skills • Being rigorous, organized, with the ability to make proposals • Being able to maintain data confidentiality • Knowing how to work in a team, under pressure and manage stress • Conducting IT monitoring

What is the ideal profile for a Data Scientist

Many schools are beginning to offer degrees in mathematics and applications with specialization in statistics, Big Data engineering, or massive data analysis. There are also other training programs that provide access to the Data Scientist profession, particularly in higher education schools for computer science, statistics, or engineering schools. However, it will still be necessary to demonstrate 4 to 5 years of experience in data analysis or in a datacenter environment.

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