Job description
Some careers have more impact than others.
If you’re looking for a career where you can make a real impression, join HSBC and discover how valued you’ll be.
HSBC is one of the largest banking and financial services organisations in the world, with operations in 62 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfil their hopes and realise their ambitions.
We are currently seeking an experienced professional to join our team in the role of Analyst- Decision Sciences
Principal responsibilities
- Undertake model validation activities as dictated by the Global Model Risk Policy including the assessment of; model inputs, calculations, reporting outputs, conceptual soundness of the underlying theory and the suitability of the use for its intended purpose, relevance and completeness of data, qualitative information and judgements, documentation, and implementation of the model.
- Provide written reports detailing the results of validations highlighting issues identified during the validation.
- Validate remediation activities completed by the ILOD to ensure appropriate resolution of identified issues.
- Communicate technical model related information and results to Model Owners and Model Users through the course of a validation.
- Contribute to management, regulatory, and external confidence in all models used across the group.
- Deliver, high quality, timely validation reports that add value to the business.
Requirements
- Worked on regulation in particular with FRTB, performed Bank wide plus desk level analysis to assess the impact of new regulation and support in quantitative impact study (QIS).
- Ensure that the FRTB IMA models meet their stated objectives by building robust risk factor eligibility test tools, NMRF SES and IMA ESF methodologies (expected shortfall methodologies)
- Have been involved in development and periodic update of proto-type models with special attention to the model related to Market risk VaR.
- Involved in creation of strategic tools for VaR/RNIV/Add-on/PnL Adjustment/Back testing using python to facilitate integration with FRTB implementation and offline calculation of risk numbers.
- Candidate should have experience in developing or validating Value at risk models using Greek based or Full Revaluation, PFE modeling for XVA, Incremental Risk charge (IRC) models etc
- Candidate should have theoretical understanding in Pricing- Derivatives/ Product Control and hedging models with focus on Interest rate, Equity, FX products
- Candidate should have experience in Stochastic Volatility modeling, calibration etc
- Minimum 1-5 years of experience of model validation/development experience in Risk Management in Market risk domain
- Must have background in financial mathematics knowledge such as stochastic calculus, numerical methods, probability theory, regression, time series analysis.
- Experience with some statistical modelling software / programming language e.g. Python, R, Matlab, C++, VBA.
- Experience of presenting recommendations to Senior Management.
- Team-oriented mentality combined with ability to complete tasks independently to a high-quality standard.
- Master’s or PhD degree in a quantitative discipline like Financial Mathematics, Statistics, Econometrics, Quantitative Finance, Economics or Engineering.
You’ll achieve more at HSBC
HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.”
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