The successful candidate will be part of a team of technical specialists to deliver solutions on the bank's key regulatory projects related to traded risk management within the Enterprise Risk Analytics function.
Key participation in designing, building and testing methodologies that consume financial market data and generate quantitative outputs.
- Research and develop methodologies to generate stress testing scenarios
- Work closely with Traded Risk managers on explaining and improving the scenario generation methodology
- Run the quarterly/daily backtesting using Standardized Initial Margin Methodology (SIMM), explain the results.
- Investigate and explain backtesting breaks.
- Design and implement the Risk not in SIMM methodology
- PhD or Master in a quantitative discipline (physics, engineering, mathematics, statistics, mathematical finance)
- Strong skills in data analytics to do explanatory and predictive analysis using statistical models.
- Experienced user of one or more programming languages (e.g. C++/C#, Matlab, Python, R).
- Knowledge of Monte-Carlo techniques, risk factor simulation modelling and derivatives pricing or any product knowledge in one or more asset classes (rates, FX, credit, equities, commodities) would be a plus.
- Prior experience in banking preferred but not a must.
- Able to communicate well with stakeholders of various levels and explain technical terms to non-technical stakeholders
If you are up for the challenge and believe you have the motivation and skills to excel in the role, please apply with your updated resume to firstname.lastname@example.org
EA Registration Number: R1871479
Argyll Scott Singapore Pte Ltd. EA Licence Number: 16S8105