Working in close partnership with other RISK teams and stakeholders (systems, reporting, regulatory, Front Office), the successful candidate will contribute to SIGMAs mission, taking responsibilities in some of the following areas:
- Participate in methodology projects, gathering and documenting requirements, considering stakeholder interests, regulatory constraints and any potential deficiencies in the current methods exposed by quality assurance processes.
- Investigate, analyse and design risk methods and models, respecting the aims of accurately capturing risks whilst considering system or other environmental constraints.
- Design, develop and test code changes required to implement the risk methods in the risk systems, whilst assisting the technical teams responsible for optimisation and promotion of the code to the production environment.
- Ensure that all methodologies, tools, processes and procedures are documented to a high standard satisfying both internal and regulatory expectations, and that any methodological changes and corresponding decision of governing bodies are promptly reflected in relevant documentation.
- Contribute to the quality assurance processes surrounding risk measurement including backtesting and VaR Adequacy (P&L Explain) process.
- Cooperate with the RISK model validation teams in the review and approval of risk models.
- Support regulatory interactions, participating in industry working groups and Quantitative Impact Studies (QIS).
- In a transactional or advisory capacity, assist risk managers and Front Office in the prompt, accurate and astute risk assessment of deals, where the standard and systematic methods may not be applicable or appropriate
Technical & Behavioral Competencies
A strong academic background, with at minimum a Masters in mathematics, physics or quantitative finance. Both Masters and Ph.Ds. are welcome.
A strong interest and familiarity with risk management best practises, financial markets and economic developments.
Experience in a quantitative finance environment, preferably in a market risk or counterparty risk modelling capacity; other backgrounds (e.g. Front Office quantitative research, model validation, hedge funds) are also welcome.
Sound understanding of stochastic processes and their application to risk factor simulations.
A practical knowledge of derivatives, their risk drivers and the models used to price them; exposure to at least one of the following asset classes: credit, repo, IR/FX, equity, commodities, preferably from a risk management perspective.
Design and implementation of quantitative models, preferably using C# or C++ in a source-controlled environment.
The role will expose the candidate to a wide range of professionals within the bank. Therefore, communication skills, both written and verbal, play an essential part of the day-to-day role. Previous experience in interacting with Front Office, validation functions and regulatory or supervisory bodies is a plus.
A good understanding and awareness of the regulatory framework for banks is desirable
Candidates expected to have PhD with further research experience.
Candidates should demonstrate proven record of research and academic excellence; published work is a plus.
More senior candidates are expected to demonstrate leadership in collaborative research projects.
The role will expose the candidate to a wide range of professionals within the bank. Therefore, communication skills, both written and verbal, play an essential part of the day-to-day role. Previous experience in joint research with other research teams is a plus.
Reasonable coding skills are expected.
In addition, a candidate from any background will have the ability to:
Work to meet tight deadlines.
Work flexibly as part of multiple teams and autonomously.
Grasp the intricacies of governance-related processes and procedures.
Juggle changing priorities and a varied workload.