We are one of the largest investment management organizations in the world, with over 1000 people working together to create long-term value.
Associate/AVP, Total Portfolio Risk Risk and Performance Management Department
The Risk and Performance Management Department is responsible for the independent assessment, measurement, monitoring and reporting of GIC's market, credit and operational risk profiles.
We are looking for a suitable candidate to join the Enterprise Risk and Performance team as an Associate/AVP. This team is responsible for reviewing the risk and performance for the GIC total portfolio across strategies and asset classes. Responsibilities
Review and improve risk frameworks for total portfolio risk management:
- Review and improve the stress testing approach for both historical and forward-looking scenarios in a factor-based, cross-asset, multi-period setting.
- Review time-varying volatility models, analyse implications, and recommend improvements to the active risk framework.
- Review sandbox for derivatives to quantify and limit model risks.
Develop risk analytics:
- Map out cross-asset correlation structures and volatility behaviour, and analyse portfolio dependencies over time.
- Develop tools to extract insights on portfolio drivers, identify concentration risks, and describe portfolios in factor-based setting.
- Build intuitive risk views which are useful for investment units and senior management.
- Document findings into research notes on a variety of risk topics.
- Singaporean citizen required due to security clearance.
- At least 3 years in a quantitative or analytical role. Experience in analysing risk factors, and modelling risks such as volatility, tracking error and stress scenarios is preferred. A working knowledge of multi-asset modelling would be assessed favourably.
- Degree in a quantitative field such as Financial Engineering, Quantitative Finance, Statistics, or Mathematics.
- Competent in analysing and manipulating time series and panel data, statistical distributions and correlations.
- Proficient in a statistical computing environment such as R or Python.
- Able to understand new concepts and processes quickly, work with moving parts, and exhibit clarity of thought.
- Good team player, while being able to independently bring projects to fruition. Motivated and driven.
- Good writing skills. Confident in presenting to stakeholders of different seniority and backgrounds.