DESCRIPTION

You will be joining the Risk and Compliance team undertaking a range of quantitative modelling and analytics to support the measurement, monitoring and management of risk, including Financial Risk models, Stress Testing, Sensitivity Analysis and a range of IFRS9 ECL modelling and reporting across our portfolios. As a Risk Analyst you will assist in our quantitative activities across our existing portfolios and any new programmes we may implement, drawing on their knowledge and experience in both R and Python coding. You will have the opportunity to gain extensive practical experience working on various quantitative modelling and analytical initiatives, progressively taking on greater responsibility which will enable you to develop your skills in a dynamic and supportive setting.
Experience
You must have knowledge and experience of R and Python coding languages is a prerequisite for this role, with a willingness to develop these skills further. Knowledge of other coding languages would be beneficial.
You will also have proficient understanding of statistical concepts and methodologies, including Ordinary Least Squares (OLS), Logistic Regression, Generalised Linear Models (GLM), Principal Component Analysis (PCA), knowledge of key statistical distributions, simulations and bootstrapping. You should have knowledge of time series models such as ARIMA, as well as hypothesis testing (e.g., t-tests, chi-square tests), ANOVA, and their key statistical assumptions and tests.
You will be able to demonstrate proficient analytical skills and attention to detail and ideally have experience/understanding of credit or investment risk management in the public or private sector.
You will be able to demonstrate technical skills in Excel and PowerPoint, with PowerBI also beneficial and have an interest in the SME finance marketplace and eagerness to learn more about the sector
Experience/understanding of credit or investment risk management in the public or private sector would be highly advantageous.
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