One of the most highly regarded teams across Quantitative Risk Analytics at a top Investment Bank in New York is looking to make an experienced hire, for a VP-level candidate to cover the entirety of the life cycle of model development for credit and counterparty risk models. This position will roll directly up to the Head of Counterparty Credit Risk Model Development and be a hands-on, technical role.
The models this hire will be responsible for developing will be quantitative models including key capital and RWA metrics such as Counterparty default loss, CVA, Impairment and standardized RWA. This hire will also be expected to maintain and enhance upon existing models already in existence, help to enhance existing frameworks and counterparty calculators, and integrate these calculations into libraries. This candidate will also be tasked with working across the firm with different business lines (model owners, IT, Analytics, etc).
Given the technical functions of the role, the firm is looking for candidates who are subject matter experts in hands-on development of risk models using Python (including scientific packages numpy and pandas). Solid understanding of risk metrics and tail statistics, as well as prior experience with counterparty risk or pricing models are needed as well.
Responsibilities:
- Development and design of quantitative risk models (Counterparty default loss, CVA, etc.)
- Maintenance and enhancement of existing frameworks and counterparty calculators
- Integrating new calculations into libraries
Qualifications:
- Master's degree in a relevant quantitative field
- 5+ years of model development experience from a hands-on perspective using Python (including scientific packages numpy and pandas)
- Programming experience in shared codebase
- Understanding of risk metrics and tail statistics
- Prior experience with software architecture
