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Quantitative Risk Modeller @
3 weeks ago
What you need to have to succeed in this role
- Knowledge of probability theory, random variables, and their distributions.
- Knowledge of Monte Carlo simulations and inference algorithms.
- Techniques for solving complex decision-making problems under uncertainty, including risk assessment and optimization.
- Sensitivity analysis to assess model robustness and uncertainty impact.
- Bayesian Networks and their applications in probabilistic modelling and graphical methods.
- Degree in a quantitative field such as mathematics, physics, computer science, quantitative finance, or a related field is mandatory.
- Proven expertise in building complex numerical simulations and analytical solutions.
- Experience in building end-to-end machine learning or analytical solutions with an emphasis on version control of data.
Your career opportunity
The Quantitative Risk Modeller will form part of the CSA Data Insight & Visualisation Team, joining a global team of data engineers, data scientists, visualisation, and risk modellers from diverse backgrounds. This role involves close collaboration with data scientists and risk modellers to build, validate, and optimize models that align with business requirements.
The Quantitative Risk Modeller is a mid-senior technical role. The job holder will lead the end-to-end development and deployment of risk models, ensuring effective risk management through data-driven methodologies at HSBC. This is an excellent opportunity for someone passionate about cybersecurity, risk modelling, and advanced analytics to contribute to a high-impact role in a dynamic environment.
If your CV meets our criteria, you should expect the following steps in the recruitment process:
- Online behavioural test
- Telephone screen
- Job interview with the hiring manager
