Quantitative IRRBB Analyst – Treasury ALM Modelling

Starling; Greater London; On-site; GBP 65,000 - 95,000; Full time

Benefits offered by this job

25 days holiday

Private Medical Insurance

Life insurance

Pension scheme

Cycle to Work

Gym partnership

Perkbox membership

Job summary

Starling Bank is seeking a Quantitative Analytics professional to join the IRRBB team in Treasury, focusing on behavioural modelling of the Bank’s evolving balance sheet. You will implement, test, and maintain models and contribute to the Bank’s quantitative Python toolset.

The role requires strong Python/SQL skills, experience in financial risk modelling, and the ability to present complex ideas to diverse audiences.

Qualifications

• Experience with economic, financial risk and/or behavioural modelling.
• Graduate level numerate degree (Maths, Physics, Economics).
• Strong data handling and programming skills.
• Excellent knowledge of Python and SQL.
• Experience with GitHub and cloud platforms (GCP/AWS).

Responsibilities

• Developing, testing, and documenting behavioural models and related processes within the Bank.
• Monitoring model performance and customer behaviour.
• Developing and expanding our internal quantitative Python library tools.
• Collaborating with IRRBB colleagues on behavioural assumption changes.
• Generating insightful analysis on Bank products and customer segments.
• Running and maintaining Interest Rate Risk models in accordance with Bank policy.
• Supporting the wider Finance team with interest rate risk hedging strategies.
• Providing quantitative modelling support throughout the Treasury team.

Skills

Python

SQL

Machine Learning

Data manipulation

GitHub

GCP

AWS

Numerical thinking

Problem solving

Presentation

Education

Graduate numerical degree (Maths/Physics/Economics)

Tools

GitHub

GCP

AWS

Job description

Starling Bank is seeking a Quantitative Analytics professional to join the IRRBB team in Treasury, focusing on behavioural modelling of the Bank’s evolving balance sheet. You will implement, test, and maintain models and contribute to the Bank’s quantitative Python toolset.

The role requires strong Python/SQL skills, experience in financial risk modelling, and the ability to present complex ideas to diverse audiences.