Manager, Analytics & Process Innovation

The role is responsible for identifying, designing, and implementing technology-driven solutions to improve Capital Markets processes, with a focus on process automation, quantitative analytics, data integration, reporting, and business intelligence. The role works with data from multiple sources to address complex business requirements, improve process efficiency and data quality, and support business decision-making. The role requires a hands-on problem solver who can independently assess business requirements, interpret business strategy and logic, and develop practical technical and analytical solutions using SQL, Python, machine learning, and data integration technologies. The role is accountable for implementing and continuously improving approved solutions, working with the Director and business stakeholders, and may lead individual initiatives or workstreams. Knowledge of AI and LLM technologies is considered an asset. Design, develop, and implement process automation solutions using SQL, Python, and other appropriate technologies to automate manual processes, improve efficiency, and reduce errors across hedging, sales activities, and day-to-day Capital Markets operations. Apply quantitative analytics and mathematical or machine learning techniques to address business problems, integrate and interpret data from multiple sources, and develop data-driven insights and recommendations to support portfolio analysis and strategy optimization. Develop and maintain reusable Business Intelligence solutions using Power BI, Tableau, or equivalent tools, including interactive dashboards and data visualizations, and apply technical judgment to improve how data and insights are presented for business decision-making. Identify opportunities to improve reporting, data controls, and reconciliations across multiple systems and data sources. Independently investigate data differences, determine root causes, assess business impacts, recommend solutions, and work with teams such as Servicing and Data Engineering to resolve material data issues. Apply business and technical judgment to complex or imperfect data, determining appropriate data rules, transformations, validation approaches, and programmatic solutions to address data limitations and meet business requirements. Evaluate and apply emerging technologies, including Generative AI, LLMs, RAG, and AI agents, where appropriate to improve automation, analytics, knowledge management, and process efficiency within Capital Markets.