Treasury IRRBB Analyst: Quantitative Analytics

Overview

In this role you will build and maintain behavioural models at the intersection of Finance, Risk and Data Science. You’ll contribute to ALM and risk modelling within a growing IRRBB team, collaborating with Treasury and Finance to inform hedging and risk decisions. You’ll advance our Python toolkit and provide clear analyses of customer segments and product performance. This is a chance to shape how Starling manage liquidity and interest rate risk through innovative modelling.

Pay / Benefits

• 25 days holiday + birthday off
• Company pension
• Life insurance (4x salary)
• Private Medical Insurance
• Perkbox discounts
• Volunteer time (16 hours)

Responsibilities

• Develop, test, and document behavioural models and related processes
• Monitor model performance and customer behaviour patterns
• Enhance internal quantitative Python toolset and libraries
• Collaborate on behavioural assumption changes with IRRBB colleagues
• Produce insights on bank products and customer segments
• Run and maintain Interest Rate Risk models per Bank policy
• Support broader Finance with interest rate risk hedging strategies
• Provide quantitative modelling support across the Treasury team

Key requirements

• Experience with economic, financial risk and/or behavioural modelling
• Knowledge of Treasury functionality (highly preferred)
• Graduate level education with numerical degree
• Strong data handling and manipulation skills
• Excellent programming in Python and SQL
• Interest in traditional statistics and applied machine learning
• Strong problem solving and quantitative skills
• Ability to distil complex ideas for broad audiences
• Experience with GitHub and cloud platforms (GCP, AWS)

• Problem solving
• Clear communication of complex ideas
• Cross-functional collaboration
• Python
• SQL
• GitHub

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