Treasury Modelling & Analytics CCAR PPNR

The primary function of this role is : to contribute to the banks balance sheet and income statement modelling methodologies in support of various end uses, such as stress testing, interest rate risk in the banking book, liquidity, and planning. The suitable candidate will have the following responsibilities in this role:

• Manage relationships with Business/Risk/Treasury/Finance model stakeholders. This involves running meetings to facilitate important model-related decisions pertaining to business line segmentation, data, model development decisions, and model choice criteria.
• Execute on model development protocols to produce models that align with the regulatory range of acceptable practices.
• Critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level information into details and abstract up from low-level information to a general understanding.
• Work independently with team leads / teams / management.
• Candidate should possess a very good English communication skill in order to coordinate and communicate their work effectively with various stakeholders spread across globe. Candidate needs to possess people skills and be able to handle complex situations.

Your key responsibilities

The position of Assistant Vice President Risk Methodology is responsible for (but not limited to):

• Contribution to model development, and the creation of robust and repeatable analytics across usages.
• Author Model Documentation and ad-hoc model analysis reports.
• Contribution to model analysis of assumptions, weaknesses, and compensating controls.
• Creating proof of concept case studies and then formalize requirements for the rollout of advanced analytics.
• Contribution to modelling advancements by exploring alternative modelling approaches.

Your skills and experience

• Experience in model development for Banking or Capital Markets at a top tier bank or consulting firm
• Solid banking business knowledge will be beneficial for this position (e.g. how do different businesses operate and generate revenues)
• Strong Experience on R Studio, and/or Python
• Degree from top tier institution with a quantitative concentration, e.g., applied statistics / mathematics, engineering, econometrics, etc.
  • The role requires strong quantitative skills, including:
  • Knowledge and modeling experience in at least one area: PPNR, Credit Risk, Market risk and relevant interdependencies
  • Familiarity with time-series, account level, and regression techniques
  • Understanding of linear and non-linear interdependence between risk factors such as variance-covariance
  • Knowledge of key distributions and their implementation in various analysis contexts
  • Proficiency in at least one programming language such as R and Python

• Strong written and verbal presentation and communication skills

Behavioral Skills:

• Collaboration and Teamwork
• Integrity, Trust and Fairness
• Effective Communication
• Professional Development Focus
• Business and product knowledge
• Leadership and Influence
• Commercial and Business Acumen
• Openness to innovation and change
• Performance orientation
• Client Relationship Focus

Educational Qualifications

• University graduate or equivalent degree in finance, economics, mathematics, statistics or engineering is a must. Masters qualifications or above would be considered an advantage.