Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo, and striving to be best-in-class.
As a Quantitative Analyst in the Market Risk Model Development team, you will help design and implement models that are critical to the firm’s risk management and regulatory compliance. You will work with a diverse group of colleagues who value your insights and support your growth. Together, we ensure our models meet the highest standards and make a real impact on the business.
Job Responsibilities
- Apply advanced statistical analysis to historical market data to specify and implement mathematical models for Value-at-Risk, regulatory capital, and stress testing of Fixed Income portfolios, with a focus on Corporate Credit and Securitized Products
- Devise statistical tests to evaluate model performance and quantify the impact of alternative modeling assumptions
- Interpret regulatory pronouncements and translate them into actionable model specifications
- Coordinate model implementation with Front Office model developers and Technology partners
- Explain model behavior to Risk managers, Trading desk personnel, and Regulators
- Establish comprehensive model documentation and liaise with Model Risk Governance and Review for model validation
- Assess model risk issues associated with valuation and risk models, and devise compensating controls when necessary
Required Qualifications, Capabilities, and Skills
- Minimum 3 years of professional experience as a quantitative analyst in model development, model validation, or quantitative risk management for Fixed Income trading, with a focus on Corporate Credit or Securitized Products
- Strong foundation in probability theory, time series analysis, and statistics as applied to financial modeling
- Proficiency in computer programming, with experience handling large datasets and using Python tools such as pandas, scipy, sklearn, and Jupyter
- Excellent verbal and written communication skills, with the ability to present complex concepts to both technical and non-technical audiences
Preferred Qualifications, Capabilities, and Skills
- Advanced degree (PhD or Masters) in Engineering, Mathematics, Physics, Finance, Computer Science, or a related field preferred
- Demonstrated curiosity about finance and a research-oriented mindset
- Experience consulting academic literature to solve practical modeling challenges
- Enthusiasm for sharing knowledge and collaborating within a team environment