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 Developer Associate within our Wholesale Credit Quantitative Research Model Implementation Team, you will be part of a mission to design, implement and deliver quantitative models to support the firm’s wholesale Credit Stress (CCAR, ICAAP, Risk Appetite, Legal Entity Risk) and Loan Loss Reserve (CECL, IFRS9) models. You will focus on design and implementation of calculation framework and related tools to enhance ease of integration of pricing and forecasting models, improve flexibility and extendibility of the framework as well as improve scalability and performance. This role will provide you with the opportunity to work with model developers, model governance and the wholesale credit business partners, enhancing your quantitative, coding, as well as business skills.
Job Responsibilities
- Design, Implement and Maintain JP Morgan’s wholesale credit models – Stress Testing (CCAR, ICAAP, Risk Appetite) and Credit Reserve (CECL, IFRS9) regulatory requirements to assess portfolio health
- Implement high performance optimized computing solutions and designs
- Implement efficient numerical algorithms using Python libraries
- Build object-oriented programs for Risk Analytics and integrate new models into the Firmwide Forecasting Framework
- Perform analysis and debugging for counter-intuitive observations in model forecasts
- Prepare technical documentation – review, implementation and testing
- Perform peer code reviews to improve the efficiency and robustness of the forecasting framework
- Partner with model developers and business during the implementation, testing and operationalization of the forecasting processes
- Present regular updates to senior management and modelers regarding latest development in the forecasting libraries implementation
- Manage project deliverables, bug fixes and new feature roll-out for ongoing model development.
Required qualifications, capabilities and skills
- Master’s Degree on a quantitative program (Math, Physics, Computer Science or Engineering) or commensurate management related job experience
- Advanced Object-Oriented Programming skills using Python, with working knowledge of common libraries including numpy and pandas
- Experience implementing analytics frameworks. Experience with source control automated build/test systems, code coverage, unit testing and release processes
- Knowledge of issue and bug tracking systems such as JIRA
- Understanding of system design and multi-process program design
- Knowledge of Data Structures and Program Design Techniques
- Knowledge of Statistical Modeling and Monte Carlo simulation
Preferred qualifications, capabilities and skills
- Knowledge of Unix Systems and Scripting
- Ability to work with large datasets and working knowledge of database systems and SQL
- Knowledge of distributed computing
- Knowledge of Wholesale Credit, CCAR, Allowance (IFRS 9/CECL), Basel II/III regulatory capital
- Proven ability to develop collaborative relationships with key internal partners to achieve objectives and prioritizations
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