Trouvez votre prochaine offre d’emploi ou de mission freelance Machine Learning

Ce qu’il faut savoir sur Machine Learning

Machine Learning (ou apprentissage automatique) est une discipline de l’intelligence artificielle qui permet aux systèmes informatiques d’apprendre à partir de données et de s’améliorer sans intervention humaine directe. Le Machine Learning utilise des algorithmes et des modèles statistiques pour détecter des motifs, effectuer des prédictions ou proposer des recommandations. Il peut fonctionner de différentes manières : avec apprentissage supervisé, où le modèle est entraîné sur des données étiquetées pour prédire des résultats spécifiques, avec apprentissage non supervisé, où il explore des données non étiquetées pour identifier des structures ou des regroupements, ou encore avec apprentissage par renforcement, où le système apprend par essais et erreurs pour maximiser une récompense. Cette technologie est utilisée dans de nombreux secteurs, comme la reconnaissance d’images, les assistants virtuels, les systèmes de recommandation ou l’automatisation industrielle, et elle joue un rôle clé dans l’exploitation des données et l’innovation technologique.

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CDD

Offre d'emploiEnterprise Data Architect

Nexus Jobs Limited
Publiée le

£40k-45k
Grand Londres, Royaume-Uni
Enterprise Data Architect As the enterprise data architect, you will own the programme pipeline for developing our data architecture strategy, including translation of our goals and objectives into enriched data dashboards. You will define and direct SXSW London's target data architecture (inc. shared data environments, data model and standards) in support of our business strategy, ensuring that data is accurate, secure and accessible to meet the needs of senior executives and department heads. Responsibilities Accountable for the data architecture & design, including implementation of company-wide data models, incorporating relevant governance frameworks, and architectural standards. Develop architectural solutions resulting in a single source of truth data lake warehouse, utilising Power Bi with built-in AI design considerations. Lead the design and development of scalable data pipelines and solutions, which support our event operations across our customer journey and channels. Collaborate with stakeholders and external technology partners to promote consistent and value driven data usage. Communicate the value of data management, through workshops and proof of concepts in partnership with business and technology partners Develop data architecture governance and standards, regarding data models and capabilities, including ability to logically model marketing and financial data. Connect disparate sources to provide seamless data access. Define KPI and Metrics for data dashboard. Map existing data sources and identity data access points. Create dedicated stakeholder UAT group for continuous output assessment. Build an executive dashboard. Configure integration and workflows. Create automation and refresh schedules. Setup training and confidence workshops. Integrating ML and AI into dashboard reporting Required Deep knowledge of modern data architecture. Experience within Cloud platforms (Azure, AWS, Databricks). Strong understanding of ETL/ELT, API's and integration patterns. Strong communication and stakeholder engagement. 5years+ in data architecture or related fields. Deep understanding of Information Security, alongside privacy and compliance regulations. Proven experience in enterprise-scale data modelling. Expertise in metadata management. Excellent analytical, planning, organisational and technical skills along with excellent written and verbal communication skills. Experience in translating complex technological requirements to an audience with minimal technical insight. This is a hybrid position based in the City of London. The position is a 6 month FTC role. The salary for this role will be circa £40K - £45K. Do send your CV to us in Word format along with your salary and availability.
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CDI

Offre d'emploiBusiness Analyst Risque de Marché / CDI / (H/F)

FINAXYS
Publiée le
Finance
Gestion des risques
Gouvernance, gestion des risques et conformité (GRC)

Boulogne-Billancourt, Île-de-France
🚀 Qui sommes-nous ? Finaxys est un cabinet de conseil spécialisé dans les secteurs Banque, Finance et Assurance. Depuis plus de 15 ans, nous intervenons auprès des plus grandes institutions telles que BNP Paribas, Crédit Agricole, Société Générale, AXA, Malakoff Humanis, etc. en proposant des solutions technologiques innovantes (IA, Machine Learning, Data, Cloud, DevSecOps, etc.). Notre mission ? Accompagner nos clients dans leur transformation digitale et répondre aux défis IT les plus complexes grâce à l'expertise de nos équipes. 🎯 Votre mission : En tant que Business Analyst Risque de Marché, vous rejoindrez les équipes techniques de nos clients grands comptes pour : Recueillir et analyser les besoins des utilisateurs Identifier et analyser les impacts des besoins utilisateurs sur les systèmes IT Participation à la définition de la solution d'implémentation fonctionnelle Rédiger les spécifications fonctionnelles au niveau projet et valider les spécifications détaillées au niveau des systèmes impactés, Participer aux différentes phases de recette : fonctionnelle, unitaires, tests UAT Former les utilisateurs Participer à la rédaction de la documentation projet Participer aux réunions avec les utilisateurs, rédiger des comptes rendus, créer des présentations
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CDI

Offre d'emploiProject Manager with Digital Banking Operations and Artificial Intelligence AI

Nexus Jobs Limited
Publiée le

Grand Londres, Royaume-Uni
Project Manager with Digital Banking Operations and Artificial Intelligence AI We are seeking a Project Manager with Digital Banking Operations and Artificial Intelligence (AI) Projects experience to join our Client a bank based in Central London. This is a full-time role located in London, with flexibility for some remote work. As an AI project manager, you be responsible for overseeing and managing the implementation of AI projects within our digital banking operations. You will collaborate with cross-functional teams to define project goals, develop project plans, allocate resources, track progress, and ensure timely and successful delivery of projects. Experience and Qualifications Previous experience in project management, preferably within the banking or financial services industry Strong understanding of digital banking operations and Artificial Intelligence AI technologies Proven track record of successfully delivering complex projects on time and within budget Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams Strong problem-solving and decision-making abilities Knowledge of agile project management methodologies Experience with data analysis and reporting Ability to adapt to changing priorities and work well under pressure Project management certification (e.g., PMP) is a plus Bachelor's degree in a relevant field Areas to Consider 1. Customer Service Enhancement Chatbots and Virtual Assistants: Deploy AI-driven chatbots to handle routine inquiries, provide 24/7 support, and reduce wait times. Sentiment Analysis: Use AI to analyze customer feedback and sentiment from various channels to improve services. 2. Fraud Detection and Prevention Real-Time Monitoring: Implement AI algorithms to detect and flag unusual transactions in real-time. Predictive Analytics: Use machine learning models to predict potential fraud based on historical data and behavioural patterns. 3. Loan Processing Automation Credit Scoring: AI can evaluate creditworthiness more accurately by analyzing a wider range of data points. Document Verification: Automate the verification of documents submitted for loan applications, speeding up the approval process. 4. Personalized Banking Services Customer Insights: Leverage AI to gain insights into customer behaviour and preferences, allowing for personalized product recommendations. Marketing Campaigns: Use AI to target customers with tailored marketing campaigns based on their transaction history and preferences. 5. Risk Management Risk Assessment: AI can analyze market trends and economic indicators to provide early warnings about potential risks. Compliance Monitoring: Automate compliance checks and monitoring to ensure adherence to regulations and reduce the risk of non-compliance penalties. 6. Operational Efficiency Process Automation: Use robotic process automation (RPA) to handle repetitive tasks such as data entry, account reconciliation, and report generation. Workflow Optimization: AI can optimize workflows by identifying bottlenecks and suggesting improvements. Implementation Strategy Assessment: Evaluate the current state of digital banking operations and identify areas where AI can add value. Pilot Projects: Start with pilot projects to test AI applications in a controlled environment. Scalability: Ensure that AI solutions are scalable and can handle increasing volumes of data and transactions. Employee Training: Train staff on AI tools and their applications to ensure seamless integration. Continuous Improvement: Regularly update AI models and algorithms based on new data and evolving business needs. Challenges and Considerations Data Quality: Ensure high-quality data for accurate AI predictions and analysis. Regulatory Compliance: Stay compliant with financial regulations while implementing AI solutions. Customer Trust: Maintain transparency in AI-driven decisions to build and maintain customer trust. Integration: Seamlessly integrate AI with existing banking systems and processes. The main emphasis of this position to is harness the data from a variety of data tables at the bank and collate a Data Lake from which to extract a variety of AI reports to increase the banks customer strategy. By strategically implementing AI in these areas, a Digital Banking Operations Manager can greatly improve the efficiency, security, and customer satisfaction in digital banking operations. The position will be hybrid 3 days a week in the office. The salary is negotiable depending on experience but probably in the range £80K - £120K plus benefits. Do send your CV to us in Word format along with your salary and notice period.
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Les métiers et les missions en freelance pour Machine Learning

Data scientist

Le/La Data Scientist utilise Machine Learning pour développer des modèles prédictifs basés sur des données complexes.

Data analyst

Le/La Data Analyst utilise Machine Learning pour automatiser l'exploration des données et identifier des tendances clés.

Développeur·euse IA/Machine Learning

Le/ La développeur·euse IA/Machine Learning est spécialisé dans la création de modèles d'apprentissage automatique pour résoudre des problèmes complexes comme la reconnaissance d'images, le traitement du langage naturel ou la prédiction de données.

Ingénieur·e R&D

L'ingénieur·e R&D conçoit et développe des solutions innovantes en s'appuyant sur les techniques de Machine Learning pour améliorer les produits ou les processus d'une organisation.

Développeur·euse data (décisionnel / BI / Big Data / Data engineer)

Le/ La développeur·euse data (décisionnel / BI / Big Data / Data engineer) implémente des modèles de Machine Learning dans des pipelines de données pour extraire des informations utiles et optimiser les processus décisionnels.

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