Find your next tech and IT Job or contract Data Scientist

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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Contractor

Contractor jobDevOps / Intégrateur Data Senior - Python & PySpark (H/F)

Insitoo Freelances
Published on
Azure DevOps
Azure Kubernetes Service (AKS)
Kubernetes

2 years
450-500 €
Lyon, Auvergne-Rhône-Alpes
Basée à Lille, Lyon, Nantes, Grenoble, Marseille, Paris et Bruxelles, Insitoo Freelances est une société du groupe Insitoo, spécialisée dans le placement et le sourcing des Freelances IT et Métier. Depuis 2007, Insitoo Freelances a su s'imposer comme une référence en matière de freelancing par son expertise dans l'IT et ses valeurs de transparence et de proximité. Actuellement, afin de répondre aux besoins de nos clients, nous recherchons un DevOps / Intégrateur Data Senior - Python & PySpark (H/F) à Lyon, France. Les missions attendues par le DevOps / Intégrateur Data Senior - Python & PySpark (H/F) : Vos missions : Construire et optimiser les pipelines CI/CD pour des applications web et des traitements Python / PySpark. Garantir le Maintien en Conditions Opérationnelles (MCO) et l'observabilité (logs, métriques) des produits. Maintenir et faire évoluer l'Infrastructure-as-Code. Administrer les environnements de dev, préprod, prod et les espaces "lab" dédiés aux Data Scientists. Gérer le traitement des vulnérabilités cyber et la montée en version des dépendances. Votre profil : Expérience : Au moins 5 ans en tant que DevOps, dont 2 ans minimum sur des projets Data Science / Machine Learning à fort volume. Stack technique : Kubernetes, Helm, Docker, GitLab CI/CD, Jenkins, Ansible, Python, PySpark, PostgreSQL, Kafka, Hadoop. Savoir-faire : Solides compétences en IaC, sécurité TLS, administration système/VM, réseaux et monitoring. Qualités : Autonomie, proactivité, rigueur et excellente communication pédagogique avec les équipes métiers et techniques. Les modalités : Lieu : Lyon Télétravail : 50 % Durée : Mission longue Démarrage : 1er janvier 2027
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Contractor

Contractor jobData Engineer SAP AI – Confirmé/Senior

HOXTON PARTNERS
Published on
AI Agent

1 year
400-550 €
Paris, France
Dans le cadre d'un programme stratégique autour de l'Intelligence Artificielle, nous recherchons un Data Engineer SAP AI capable d'intervenir sur la conception, l'intégration et l'exploitation de données issues de SAP S/4HANA, afin d'alimenter des cas d'usage Data & AI à forte valeur métier. La mission nécessite une présence sur site à Paris 3 jours par semaine. Missions principalesConcevoir et développer des pipelines de données à partir de SAP S/4HANA. Extraire, transformer et intégrer les données SAP vers des plateformes Data. Participer à la mise en œuvre de cas d'usage IA / GenAI exploitant les données SAP. Garantir la qualité et la fiabilité des données. Collaborer avec les équipes métiers, Data Scientists, Data Engineers et Architectes Data. Optimiser les performances des flux de données et traitements analytiques. Préparer et mettre à disposition les données pour les modèles IA. Compétences recherchéesSAP Expertise SAP S/4HANA Bonne compréhension des données et processus métiers SAP Expérience en intégration et extraction de données SAP Data Engineering SQL avancé Python Spark ETL / ELT Data Lake / Data Warehouse APIs et traitements de données AI / Analytics Connaissance des architectures IA et GenAI Préparation des données pour les modèles IA Compréhension des enjeux RAG, LLM et gouvernance des données appréciée Cloud Azure, AWS ou GCP apprécié ModalitésType de mission : Assistance technique / Expertise Data Localisation : Paris Présence : 3 jours/semaine sur site Démarrage : ASAP Durée : à confirmer
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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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