Experience, knowledge and qualifications: Bachelor's Degree in Computer Science, Information Technology, Business Administration, Data Science, Engineering, or a related field. Must have experience: Risk, CDD, AML, Fatca, regulatory experience Advanced degree or relevant certifications will be advantageous, including: CBAP (Certified Business Analysis Professional) PMI-PBA Agile Certifications AI or Data Analytics Certifications 8+ years' experience as a Business System Analyst, with a strong background in financial services, investments, or wealth management. Proven experience leading complex system analysis and business transformation projects. Experience working on digital transformation, automation, analytics, or AI-related initiatives. Experience with enterprise applications, data integration, and reporting solutions. Exposure to AI, Machine Learning, Robotic Process Automation (RPA), Generative AI, or advanced analytics solutions will be highly advantageous. Competencies & skills: Business Analysis: Advanced analytical and problem-solving skills. Strong understanding of business processes, systems analysis, and requirements management. Expertise in business process modelling and optimization methodologies. AI & Digital Capabilities: Ability to identify, evaluate, and define AI use cases and business value opportunities. Knowledge of Responsible AI principles, AI governance, ethics, privacy, and risk management. Technical Skills: Proficiency with business analysis and collaboration tools such as Microsoft Visio, JIRA, Confluence, Azure DevOps, and Microsoft Power Platform. Familiarity with data visualization and reporting tools such as Power BI. Knowledge of Agile, Scrum, BPMN, UML, and system design methodologies. Experience working with cloud platforms and AI services (AWS, Microsoft Copilot, or equivalent) will be advantageous. Leadership & Stakeholder Management: Excellent communication, facilitation, and presentation skills. Ability to influence decision-making and engage stakeholders at all organizational levels. Strong project leadership and vendor management capabilities. Ability to manage multiple initiatives simultaneously while maintaining a high standard of quality and delivery. Key Responsibilities: Business Process Analysis & AI Enablement: Conduct comprehensive analysis of business processes, systems, and data flows to identify inefficiencies, risks, automation opportunities, and areas for AI-driven enhancement. Collaborate with business units to understand strategic and operational needs and translate them into actionable business, system, data, and AI requirements. Assess business processes for suitability for intelligent automation, machine learning, predictive analytics, natural language processing (NLP), and generative AI solutions. Facilitate AI use case discovery workshops to identify opportunities that improve operational efficiency, customer engagement, investment decision support, and risk management. Develop and maintain comprehensive documentation for business processes, system requirements, AI requirements, and functional specifications. System Design, AI Solutions & Implementation: Design and develop business system solutions that align with organizational objectives and emerging technology strategies. Partner with enterprise architects, developers, data scientists, and AI specialists to integrate AI-powered capabilities into business applications and workflows. Evaluate AI platforms, intelligent automation solutions, and digital tools to determine their suitability for business requirements. Support the implementation of AI-enabled solutions such as: Intelligent document processing Predictive analytics models Robotic Process Automation (RPA) Conversational AI/chatbots Generative AI-assisted business processes Work closely with IT teams to ensure successful implementation of system enhancements, upgrades, and new features. Review and participate in testing activities, including functional, integration, user acceptance testing (UAT), and validation of AI model outputs to ensure accuracy, reliability, fairness, and compliance.