Corporate - Model Risk Governance & Review - Model Review Group - Associate
- Recruiter
- JP Morgan..
- Location
- Jersey City, NJ, USA
- Salary
- Competitive salary
- Posted
- 11 Nov 2019
- Closes
- 26 Nov 2019
- Ref
- 6732407
- Job role
- Accountant
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.
Associate-level role in the Model Review Group (MRG) of JPMorgan
The Model Risk Governance and Review Group (MRGR) oversees model risk at JPMorgan, conducts independent model reviews and provides guidance around a model's appropriate usage. The Model Review Group (MRG) is a part of MRGR and is tasked with assessing and mitigating the risk posed by models used to:
The Associate-level position requires the successful candidate to 1) quantitatively evaluate complex econometric / mathematical forecasting models, and 2) build benchmark models in the process of evaluating (1). The position is located in New York, NY.
Core responsibilities
Desirable skills, experience, and qualifications
Associate-level role in the Model Review Group (MRG) of JPMorgan
The Model Risk Governance and Review Group (MRGR) oversees model risk at JPMorgan, conducts independent model reviews and provides guidance around a model's appropriate usage. The Model Review Group (MRG) is a part of MRGR and is tasked with assessing and mitigating the risk posed by models used to:
- value exposures and measure market, credit and liquidity risk for securities held by the Bank
- forecast assets, fees, credit losses, interest income to assess adequacy of capital under stress
- analyze business strategies and inform business decisions.
The Associate-level position requires the successful candidate to 1) quantitatively evaluate complex econometric / mathematical forecasting models, and 2) build benchmark models in the process of evaluating (1). The position is located in New York, NY.
Core responsibilities
- Assess statistical, economic, financial, or mathematical theories and techniques applied.
- Verify that models are performing as expected, in line with their design objectives and business uses.
- Evaluate conceptual soundness of econometric and mathematical model specification; reasonableness of assumptions; reliability of inputs; completeness of testing performed; correctness of implementation; and suitability / comprehensiveness of performance metrics and risk measures.
- Design and implement experiments to measure the potential impact of model limitations, parameter estimation errors or deviations from model assumptions; compare model outputs with empirical evidence and/or outputs from model benchmarks.
- Liaise with front office, Finance and Risk professionals to monitor usage and performance of the models.
- Help senior MRG researchers evaluate econometric and mathematical models developed by all lines of business including the retail bank, commercial bank, investment bank, asset management
- Evaluate market conditions under which a given model is likely to break down.
- Identify market risks most relevant to the Bank's various lines of business.
- Cogently document findings.
Desirable skills, experience, and qualifications
- The candidate is expected to be self-driven, have basic understanding of risk analysis and have interest in economics and finance.
- A Ph.D. or master's degree in a quantitative field such as Finance, Economics, Math, Physics or Engineering is required.
- 0-3 years of experience
- Thorough knowledge of at least one programming language such as R, Python, Matlab, C/C++, etc. is required.
- Deep understanding of statistics / econometrics
- Communication skills are important since the role requires interacting with many groups across the firm as well as producing documents for both internal and external (regulatory) consumption.
- Familiarity with AI/ML methods is preferred.