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Quantitative Analyst - AVP/VP

  • Location

    London, United Kingdom

  • Sector:

    Financial Services and Banking

  • Job type:


  • Contact:

    Charlie Morris

  • Contact email:

  • Salary high:


  • Salary low:


  • Published:

    3 months ago

  • Expiry date:


On behalf of our client, an international bank:

As a Quantitative Analyst AVP/VP within Treasury Modelling, you will help to design, build and deliver robust and production quality models implemented within a unified library. You will also assist with the systematic review and on-going assessment of existing models for forecasting asset and liability behavioural balances and resulting net interest income. 

What will you be doing?
• Contributing to the development and implementation of key Treasury models, including driver-based models for projecting the banks' balance sheet
• Delivering high quality documentation and presentations to support and maintain model and library use
• Facilitating and having challenging discussions about modeling options with model owners and other stakeholders
• Supporting the development of user tooling for management decision making within Global Treasury
• Supporting the quantification of funding and capital plans and forward-looking impairments
• Measuring of liquidity and funding risk associated with the bank’s asset/liability profile.
• Supporting model development for quantification of interest rate risk on the banking book (ALM models, hedging models, prepayment models).

What we’re looking for:
• Industry experience in quantitative finance or relevant academic or industrial experience
• Good understanding of financial modelling techniques
• Proficiency in Python
• Ability to deliver to tight deadlines on quantitative projects and to manage the end to end process of model delivery

Skills that will help you in the role:
• Experience in designing and developing mathematical financial, in particular statistical, models
• Good understanding of library and code design
• Experience in fixed income derivatives and interest rate curve construction
• Experience in analysing large volumes of data, including cleaning and subsequent pattern identification and clustering