Posting Description:
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.
MRGR is a global team of modeling experts within the firm's Risk Management and Compliance organization. The team is responsible for conducting independent model validation and model governance activities to help identify, measure, and mitigate Model Risk in the firm. The objective is to ensure that models are fit for purpose, used appropriately within the business context for which have been approved, and that model users are aware of the model limitations and how they could impact business decisions.
The Model Risk Governance & Review (MRGR) group is responsible for conducting model validation and governance through the model lifecycle to help identify, measure, and mitigate Model Risk. The objective is to ensure that models are used appropriately in the business context and that model users are aware of the models' strengths and limitations and how these can impact their decisions. MRGR works closely with Risk, Finance, Control and LOB professionals to monitor model performance, review findings, and implement risk mitigating strategies.
Job Responsibilities:
- The successful candidate will be a member of the MRGR group for CCB and will lead a team of individuals on the validation and risk governance of Marketing models used across CCB. This is a great role, with the right platform to grow.
- Will lead model validation of Machine Learning(ML) marketing models within CCB, will be proficient in the technical aspects of ML, will understand strengths and limitations of ML models, will have a practitioner's understanding of the regulatory requirements for ML models, and will be able to articulate whether the choice of an ML technique is appropriate. S/he will also be proficient in the standard tools and languages of ML.
- Will carry out model validation, including model reviews and model risk measurement:
- Model reviews: evaluate conceptual soundness of model specification; reasonableness of assumptions and reliability of inputs; completeness of testing performed to support the correctness of the implementation; robustness of numerical aspects; suitability and comprehensiveness of performance metrics and risk measures associated with use of model.
- Model risk measurement: design and implement experiments to measure the potential impact of model limitations, parameter estimation error or deviations from model assumptions; compare model outputs with empirical evidence and/or outputs from model benchmarks.
- Keep up with the latest developments in CCB/industry in terms of modeling techniques (advanced AI/ML methodologies) products, markets, models, risk management practices and industry standards.
- Assist in training junior members of the team and facilitate their learning and development.
Minimum Skills, Experience, and Qualifications:
- PhD or Masters degree in quantitative disciplines such as Computer Science, Applied Maths, Economics, Statistics, Physics, Engineering or similar.
- 10+ years of relevant experience, with at least 5+ years of experience in applied quantitative research or model development for retail financial products, including machine learning experience, with demonstrated leadership excellence.
- In depth knowledge of machine learning techniques (supervised and unsupervised), natural language processing, data mining as well as experience in probability theory, econometrics, statistics, numerical methods.
- Product domain expertise in retail products and ability to understand the business / knowledge of regulation surrounding business
- Excellent analytical and problem solving abilities.
- Risk & Control mindset: Inquisitive nature, ability to ask right questions and escalate issues.
- Excellent communication skills (written and verbal).
- Experience managing teams
