Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Hello, we’re Starling. We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way. We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,500 people across our London, Southampton, Cardiff and Manchester offices. This role sits in the Quantitative Analytics pillar of the IRRBB team within Treasury. We are a small but growing team that focuses on behavioural modelling of the Bank’s evolving balance sheet. We are at the intersection of Finance, Risk and Data Science, combining aspects of all three disciplines in our work and acting as technical experts with deep financial and programming skills. The IRRBB team is part of Treasury, where we manage liquidity, funding, interest rate risk and structural risks using cash, investment securities, interest rate derivatives and foreign exchange. The Analyst will primarily focus on ALM but will also have the opportunity to closely collaborate with other Treasury areas through their modelling work. This is a permanent role in the team to continue building capacity, and you will be a key driver in the development, implementation, and maintenance of the behavioural models used throughout the Bank.

Key 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

Experience
Experience with economic, financial risk and/or behavioural modelling
Knowledge of Treasury functionality is highly preferred

About you
A problem solver with strong quantitative skills
The desire to use both traditional statistical modelling and applied machine learning
Ability to distil complex ideas for presentation to a broad audience
Strong technical skills in data handling and manipulation
Excellent programming knowledge, particularly in Python and SQL
Experience with developer tools such as GitHub and cloud platforms like GCP or AWS

Qualifications
Graduate level education with a numerical degree (e.g. Maths, Physics, Economics)