Portfolio Management Associate, Data & Analytics

Key Responsibilities

• Own portfolio monitoring for our capital mandates end to end — write the code that produces the numbers, then own the read on what they mean and what we should do about it
• Build and automate the monitoring and reporting that tracks performance, covenant headroom and facility utilisation, replacing manual processes with pipelines that run themselves
• Design the dashboards and visualisations that senior executives, lenders and investors rely on, and stand behind the accuracy and the commentary that goes with them
• Assess and manage the performance of underlying capital mandates: vintage and cohort analysis, loss curves, yield and advance-rate decomposition, and the early-warning indicators that flag problems before month end
• Build the scenario and sensitivity analysis — stress cases, downside macro scenarios and structural what-ifs — and interpret the output to inform capital allocation, facility sizing and pricing decisions 
• Develop and maintain cashflow and waterfall models supporting portfolio decision-making, new facility structuring and refinancing
• Write production-quality SQL and Python and build database tables and dbt models alongside our data engineering teams, so that monitoring is self-serve rather than a recurring manual task
• Bring engineering discipline to analytical work — version control, code review, testing and documentation — and help set that standard across the team
• Translate analysis into a clear recommendation: identify the trend, size the impact, and communicate it directly to senior stakeholders and external counterparties

Skills, Knowledge & Expertise

• 3–5 years of experience in data analytics, capital markets, structured finance, credit risk or a comparable quantitative role — ideally within Finance or FinTech
• Strong academic background including at least a Bachelor's degree (Mathematics, Engineering, Statistics, Computer Science, Computational Finance, Economics) or equivalent
• Advanced, hands-on SQL and Python — you build and maintain analytical code and automation yourself rather than specifying it for someone else
• The analytical judgement to go with it: you can interpret what you have built, spot when a number is wrong, and know when a model is answering the wrong question
• Demonstrated experience with data visualisation tools (e.g. Tableau, Power BI, Looker), including building and owning dashboards that other people depend on 
• Solid grounding in financial analysis and cashflow modelling - Exceptional communication skills, with a track record of delivering insight to diverse and senior stakeholders