Au sein d'une équipe d'opérations de marchés, vous prenez en charge le cycle de vie des confirmations sur produits dérivés et vous en automatisez la production. Au quotidien, vous émettez et suivez les confirmations et avis de paiement, vous rapprochez les retours signés des contreparties et vous traitez les anomalies. En parallèle, vous faites évoluer les modèles de documents de confirmation : Vous analysez le besoin des opérationnels Vous concevez les nouveaux modèles Vous alimentez leurs champs à partir de flux XML Vous les testez avant leur mise en service Vous formalisez les procédures et vous accompagnez des collaborateurs basés à l'international dans la prise en main de l'outil.
Analyser et concevoir : étudier les besoins, challenger l'éligibilité RPA, évaluer la faisabilité technique et contribuer au chiffrage, aux risques et au ROI. Développer : réaliser des automatisations avec UiPath Studio en appliquant les standards de l'équipe, notamment modularité, réutilisabilité, gestion des exceptions, logs et paramétrage. Industrialiser : concevoir des solutions adaptées aux robots attended et unattended, utiliser Orchestrator pour les assets, files, déclenchements, environnements et déploiements. Tester et documenter : préparer les tests unitaires et d'intégration, contribuer à la recette, corriger les anomalies et produire les dossiers de conception, procédures d'exploitation et éléments de traçabilité. Déployer et sécuriser : préparer le packaging, le versioning et les mises en production en lien avec les équipes Ops, architecture et SSI, dans le respect des habilitations et de la gestion des secrets. Exploiter et maintenir : superviser les exécutions, analyser les logs, diagnostiquer les incidents, assurer les corrections et évolutions, et contribuer à la stabilisation des robots. Collaborer : participer aux revues de code, aux communautés de pratique et au partage de composants, templates et bonnes pratiques. Contribuer à la transformation : participer à la migration de robots Blue Prism vers UiPath et, selon les cas d'usage, à l'intégration d'API, de traitement documentaire intelligent ou de capacités agentiques. Analyse de faisabilité et contribution au chiffrage. Conception technique et documentation PDD/SDD selon l'organisation du projet. Workflows UiPath versionnés, testés et revus. Jeux et preuves de tests, dossiers de mise en production et runbooks. Logs, tableaux de suivi, diagnostic d'incidents et plans de correction. Composants réutilisables, documentation et retours d'expérience partagés avec la communauté RPA
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.
