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 Data Scientist "H/F" à Lille, France. Contexte : Au sein de la DSI, l'équipe DIAG (Data-Intelligence Artificielle-Gouvernance) accompagne les métiers sur les sujets autour de la DATA & l'IA. Une de ces missions est de créer de la valeur par le développement et l'adoption de projets DATA/IA à fort ROI. Les missions attendues par le Data Scientist "H/F" : 1. Exploration, conception et développement de solutions IA end-to-end : - Compréhension et traduction des besoins métier : - Collaborer activement avec les métiers pour identifier les opportunités d'application de l'IA et traduire les problématiques business en cas d'usage IA. - Participer à la définition des objectifs, des KPIs et des livrables pour chaque projet. - Faire preuve d'écoute et de pédagogie pour expliquer les capacités et les limites de l'IA aux parties prenantes non techniques. - Conception et élaboration des modèles IA (Machine Learning & Générative) : - Réaliser l'exploration de données, le feature engineering, la sélection des datasets pertinents et l'analyse exploratoire. - Concevoir, développer et entraîner des algorithmes de Machine Learning et des modèles d'IA Générative (LLMs, embeddings, RAG, fine-tuning).. 2. Industrialisation et déploiement des solutions IA : - Prendre en charge l'industrialisation des modèles, depuis le développement d'APIs pour les exposer, jusqu'à leur intégration dans les systèmes existants (applications web, backend). - Mettre en œuvre les bonnes pratiques MLOps pour automatiser le déploiement, le monitoring et la maintenance des modèles en production. - Garantir la performance, la scalabilité et la sécurité des solutions IA déployées. - Monitorer les performances des modèles en production, détecter les dérives et mettre en place des plans de réentraînement ou d'ajustement. 3. Contributions et responsabilités d'appuis : - Garantir que les solutions IA apportent une valeur ajoutée mesurable aux métiers et à l'entreprise. - Participer à la capitalisation des connaissances et au partage des meilleures pratiques au sein de l'équipe - Collaborer étroitement avec les métiers et les Product Owners pour la définition des besoins et l'intégration des solutions. - Travailler en synergie avec les Data Engineers pour l'accès et la préparation des données, et avec les AI Engineers pour l'utilisation des infrastructures IA.
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.
Data Scientist – Manchester Our Client an international organisation is looking to recruit a Data Scientist with 7 to 10 years expertise as a Data Scientist. You will have Natural Language Processing (NLP) knowledge and experience and understand and analyse large data sets to discover new insights. Working in a multi-disciplinary team within a highly technical and complex environment. Well versed in scalable data mining and machine learning techniques (using computers to improve as well as develop algorithms)Kernel Methods, Deep Learning, Statistical Relational Learning, Ensemble Methods Model using advanced statistical/ mathematical models, predict and segment data to hypothesize/ evolve uses cases to monetize data and generate other business value. Translate business needs to technical requirements and implementation. Experience of Big Data technologies/Big Data Analytics. C++, Java, Python, Shell Script R, Matlab, SAS Enterprise Miner Elastic search and understanding of Hadoop ecosystem Experience working with large data sets, experience working with distributed computing tools like Map/Reduce, Hadoop, Hive, Pig etc. Advanced use of Excel spread sheets for analytical purposes MSc or PhD in Data Science or an analytical subject (Physics, Mathematics, Computing) or other quantitative discipline The position is based close to Manchester. The salary for this position will be circa £75K - £85K plus benefits. Please send your CV to us in Word format along with salary and availability details.
