CIB QR - Quantitative Research – Operational Risk – Risk Model Development – Vice President
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $2.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small business, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world's most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. QR Operational Risk (QROR)
is a team within the Quantitative Research (QR) organization of JPMorgan. QROR owns the design, implementation, and development for a broad spectrum of risk models, primarily in the measurement of regulatory operational risk capital, economic operational risk capital and operational risk stress loss (CCAR/DFAST). The Role:
This is an experienced quantitative role focused the firm's risk engines for operational risk measurement and management. The team works closely with other model development teams in QR, with teams in corporate and line-of-business operational risk management and corporate technology.
Communication skills are important to us: given the importance of capital modeling, we are seeking candidates who are able to present technical topics to senior internal stakeholders, and who are able to write high-quality model documentation.
Candidates should be comfortable collaborating with colleagues at varying levels of experience and backgrounds. Core responsibilities:
- Support production runs, analytical explains, improvements to the Regulatory Capital Models Approach (AMA), Stress Loss (CCAR/DFAST) models and supporting documentation.
- Research, development and implementation of new initiatives of risk models in the operational risk space e.g. economic capital model, cyber-risk quantification.
- Act as QROR liaison for Regulatory Capital and CCAR/DFAST models, interfacing with corporate operational risk, model review group, audit and corporate technology.
- 3 work experience, with advanced degree (PhD/MS) instatistics/mathematics/engineering/operations research
- Work experience in Risk Modeling/Stress Loss Modeling/LOB Operational RiskAnalytics in financial industry
- Expertise in statistical modelling
- Expertise in Python/C++/R; hands-on as part of work experience
- High quality communication and inter-personal skills