New York, NY, United States
11 hours ago
Risk Management - Model Risk Governance and Review Lead for Compliance Anti-Money Laundering and KYC - Senior Vice President

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 Senior VP in Model Risk Governance & Review you will lead a team of 4 globally conducting review and governance activities related to Compliance Anti-Money Laundering and KYC.

As a lead for the MRGR Compliance AML KYC team, you will oversee the model review process, development of the benchmarking tools for independent testing and ongoing performance monitoring activities around sanctions screening, trade surveillance, transaction monitoring, and over models used within Compliance. 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. You will lead a global team of 4 professionals spread across New York, New Jersey and Bengaluru. Your mandate as lead is to ensure high quality review and governance activities for this space and be the lead for communication of key risks in this space to external and internal stakeholders.

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

Set standards for robust model development and testing practices and enhance them as needed to meet evolving industry standards. Lead the team in evaluating adherence to development standards including soundness of model design, reasonableness of assumptions, reliability of inputs, completeness of testing, correctness of implementation, and suitability of performance metrics.  Lead the team in identifying weaknesses, limitations, and emerging risks through risk assessments, independent testing, developing and implementing benchmark models, and ongoing monitoring activities. Lead risk assessments and communication of model risks to senior stakeholders (internal and external), and documentation of high-quality validation reports. Lead interactions for this space during model-related audits and regulatory examinations. Stay abreast of industry best practices, regulatory developments, and advancements in AML space to guide the team and enhance validation methodologies.  Retain, develop and recruit high-performing talent. 

Required qualifications, capabilities, and skills

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 (e.g. 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, etc.). Ability to implement benchmarking models in Python, R, or equivalent. Risk- and control-oriented mindset: ability to ask incisive questions, assess the materiality of model issues, and escalate issues appropriately. Strong project management and organizational skills: flexible and adaptable to shifting priorities to achieve the most effective results. Ability to work in a fast-paced, results-driven environment & Ability to engage with senior business stakeholders and model developers and challenge them effectively. Proven ability to manage a team effectively across multiple locations and geographic time zones. Experience with regulatory standards and guidelines related to model risk management, such as SR 11-7 or similar frameworks.

Preferred qualifications, capabilities, and skills

Prior experience in modeling, reviewing or managing models for sanctions screening, trade surveillance or transaction monitoring is desirable. Experience with database interfacing, data management, and preprocessing (e.g. SQL or kdb+, q) is a plus.

 

 

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