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My client, a reputable investment bank is looking for quantitative analyst/statistical modeller or Python quantitative developer to join their Financial Modelling Quant team.
Design, build and deliver robust and production quality statistical models and code within a unified library
Deliver high quality documentation and presentations to support and maintain model and library use.
Ensure delivery of robust python code to support model orchestration for CCAR and IFRS9.
Assist with the systematic review and on-going assessment of existing models for forecasting asset and liability behavioural balances.
Assist with development of statistical models for projection of the company's balance sheet under different macro-economic scenarios.
Support quantification of the bank's funding and capital plans, forward looking impairments and pricing of liquidity and funding risk associated with the bank's asset / liability profile.
Liaise with business stakeholders to ensure that model requirements are met and implemented successfully in a production environment.
Post graduate degree in a quantitative/numerical discipline with a statistics or computer science component.
Good wholesale credit risk modelling (PD, LGD, EAD) or statistical modelling experience
Strong industry experience in quantitative finance. This may be replaced by relevant academic or industrial experience in statistics or computer science.
Good understanding of statistical and econometric modelling techniques - e.g. time series analysis, regression models and various estimation techniques.
Able to deliver to tight deadlines on quantitative projects.
Proficient in Python (preferred) or R
Good understanding of library and code design.
Knowledge of CCAR and IFRS9 is a plus.
Please send your CV to firstname.lastname@example.org
Please note our advertisements use PQE/salary levels purely as a guide. However we are happy to consider applications from all candidates who are able to demonstrate the skills necessary to fulfil the role.