Model Risk Analyst

As a Model Risk Program Analyst in Model Risk Governance & Review you will be conducting review and governance activities related to Compliance Anti-Money Laundering and KYC. Bring your expertise to JPMorganChase. As part of Risk Management and Compliance, you are at the center of keeping JPMorganChase 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 Model Risk Program Analyst you will be responsible for assessing the risks associated with models used for sanctions screening, trade surveillance, transaction monitoring, and over models within Compliance. You will perform independent testing, develop benchmarking tools, and monitor performance of the models. You will leverage your technical expertise and intellectual rigor to assess conceptual soundness of the data-driven compliance models, identify and assess the emerging model risks from various component models and model-to-model interactions. Model Risk Governance Review 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 they have been approved, and that model users are aware of the model limitations and how they could impact business decisions. Job responsibilities Perform model reviews: analyze the conceptual soundness of compliance model and assess model behavior and suitability in the context of usage.  Guide on model usage and act as the first point of contact for the business on all new models and changes to existing models. Develop and implement alternative model benchmarks and compare the outcome of various models. Design model performance metrics. Liaise with model developers, users, and compliance groups, and provide guidance on model risk. Evaluate model performance on a regular basis. Execute model governance activities such as Ongoing Performance Monitoring, and others. Required qualifications, capabilities, and skills 0-2 years of experience in a quantitative modeling role, such as Data Science, Quantitative Model Development, Model Validation, or Technology focused on Data Science. A PhD or Master’s degree in a quantitative field such as Mathematics, Physics, Engineering, Computer Science, Economics or Finance is required. Strong verbal and written communication skills, with the ability to interface with other functional areas in the firm on model-related issues and write high quality technical reports.  Deep understanding of standard statistical techniques, such as regression analysis. Hands-on experience with standard Machine Learning models, including Boosted Trees, Neural Networks, SVM, and LLM (. BERT). Experience of working with dedicated ML packages, such as TensorFlow or similar, as well as data processing and numeric programming tools (NumPy, SciPy, Pandas, . Ability to implement benchmarking models in Python or equivalent. Risk- and control-oriented mindset: ability to ask incisive questions, assess the materiality of model issues, and escalate issues appropriately. Ability to work in a fast-paced, results-driven environment. Preferred qualifications, capabilities, and skills Prior experience in modeling, reviewing or managing models for sanctions screening, trade surveillance or transaction monitoring is desirable.