Job: Senior Quantitative Risk Analyst
Location: Dublin 4
- A bachelor’s degree in a quantitative analytical discipline (2.1 or higher), e.g. mathematics, applied mathematics, physics, statistics, engineering, econometrics, operations research;
- 3+ years’ experience working in one of the following areas: predictive modelling, fraud analytics or decision optimisation algorithms;
- Advanced experience of SAS or other analytics languages (e.g. R, Python, Matlab);
- Advanced knowledge in extracting, transforming, and cleaning data for modelling purposes
- Knowledge of banking and in particular risk-adjusted return methodologies would be advantageous;
- Experience training and managing the day to day tasks of junior team members.
- Predictive modelling to estimate the likelihood of borrowers meeting their repayment obligations;
- Using data analytics and pattern recognition techniques to identify potentially fraudulent applications;
- Implementing optimisation algorithms to determine risk appetite and pricing for portfolios;
- Working closely with colleagues across the Business, the Chief Data Office, Credit Risk and IT to build, implement and monitor automated strategies.
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