About the role...
You'll work closely with the Head of Portfolio Management to build the analytical infrastructure, reporting, and commercial insight that drives portfolio strategy, pricing decisions, and business performance. Core role will include:
- Commercial analysis & automated reporting
- Track portfolio performance metrics, translating data into clear narratives that support portfolio strategy and business planning.
- Conduct risk based analysis across the portfolio — flagging emerging concentrations, pricing misalignments, and credit trends before they become problems.
- Design, build, and maintain automated Power BI dashboards and Excel solutions delivering commercial insights across all business levels.
- Develop and optimise SQL queries to extract, transform, and model data from multiple sources for financial and operational analysis.
- Create scalable, high-performance data models balancing technical robustness with business usability.
- Stakeholder engagement & communication
- Partner with finance and commercial teams to gather requirements and translate business questions into analytical solutions.
- Present data-driven insights, recommendations, and narratives to diverse audiences from operational teams to senior leadership.
- Deliver training and ongoing support to build organisational data literacy and enable self-service analytics adoption.
- Proactively enhance existing reports, optimise processes, and expand analytics capabilities.
- Contribute to the strategic evolution of the data analytics function.
- 5+ years' experience across one or more of: FP&A, treasury, pricing, sales analytics within financial services or asset finance.
- Strong analytical and problem-solving skills with the commercial instinct to turn insight into action.
- Advanced Power BI expertise including data modelling, DAX formulas, and dashboard design.
- Strong SQL proficiency including writing, optimising, and troubleshooting complex queries.
- Excellent communication and stakeholder engagement skills across all organisational levels.
- Tertiary qualification in Finance, Accounting, Economics, Mathematics, Computer Science, or related STEM field.
- Understanding of data warehouse concepts, ETL processes, and orchestration tools (Microsoft Fabric, Azure Data Factory).
- Curiosity and practical exposure to AI tools, with an appetite to explore how emerging technologies can improve analytical processes.
- Working knowledge of Python, R, or other analytical programming languages.
