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 ASSISTANT VICE PRESIDENT- 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(Line of Defense) to ensure appropriate resolution of identified issues.
  • Work with relevant stakeholders to support the embedding of new Global Model Risk Policies and Procedures. 
  • Provide coaching and guidance to new starters and junior colleagues.
  • Deliver, high quality, timely validation reports that add value to the business.
  • Communicate across technical quantitative, business and strategic levels to ensure that stakeholders understand the implications of model risks and limitations.
  • Contribute to management, regulatory, and external confidence in all models used across the group.

Requirements
  • Candidate should have worked on Wholesale AIRB models and have strong understanding of Wholesale IRB Model Development/Validation (PD, LGD, EAD and Slotting models).
  • Candidate should understand different wholesale portfolios such as Corporate, Banks, Sovereign, NBFI’s, SME, MME and Large and global enterprises etc. Candidate should be able to validate models used for different regulatory perspective such as OCC/FRB, EBA Guidelines and PRA regulations.
  • Strong statistical knowledge with hands on working experience in various modelling techniques such as linear regression, logistic regression, time series modelling, etc. 
  • Sound understanding on Basel/CRR/ECB guidelines. Sound understanding of Calibration methods and Margin of conservatism (MOC) framework while developing Wholesale IRB models.
  • Minimum 5-10 years of experience of model validation/development experience in Risk Management in Wholesale IRB domain
  • Experience with strong statistical modelling software / programming language e.g., Python, SAS, R, VBA, Matlab.
  • Experience of presenting recommendations to Senior Management. Experience of conducting independent model reviews
  • Ability to present complex statistical concepts and results to non-technical audiences in a persuasive and compelling manner.
  • 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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