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This job is responsible for leading a team to develop or validate quantitative analytics and models for specific business units or risk types. Job expectations include supporting business units and acting as a subject matter expert on specified quantitative modeling techniques, as well as serving as the first or second line of defense overseeing model performance, model risk, and model governance on critical model portfolios.
Responsibilities:
Leads a quantitative team with model coverage of specified focus areas and oversees stakeholder engagement, including team effort in preparation for audit and regulatory exams
Sets priorities related to quantitative modeling in line with the bank’s overall strategy and prioritization
Identifies continuous improvements through reviews of approval decisions on relevant model development or model validation tasks, critical feedback on technical documentation, and effective challenges on model development/validation
Maintains and provides oversight of model development and model risk management in respective focus areas to support business requirements and the enterprise's risk appetite
Leads and provides methodological, analytical, and technical guidance to effectively challenge and influence the strategic direction and tactical approaches of development/validation projects and identify areas of potential risk
Works closely with model stakeholders and senior management with regard to communication of submission and validation outcomes
Model Validation Lead (“MVL”) oversees the team conducting independent validation and analytics for AML models. The MVL is responsible for providing risk oversight, acting as a subject matter expert and the second line of defense overseeing model performance, model risk and model governance. The MVL provides advice and counsel to the LOB and Risk Partners and is expected to help establish model risk management policies, limits, standards, controls, metrics and thresholds within the model risk framework. Accountable for managing execution of model risk framework activities including, but not limited to, independent validation and ongoing monitoring reviews for models for the LOB. The candidate should exhibit familiarity with industry practices and have knowledge of up-to-date AML techniques. The candidate should be able to provide both thought leadership and hands-on expertise in methodology, techniques, and processes in applying statistical and machine learning models to manage the bank’s AML models and model systems.
The position will be responsible for:Minimum Education Requirement: Master’s degree in related field or equivalent work experience
Required Qualifications & Skills:
• PhD or Masters in a quantitative field such as Mathematics, Physics, Finance, Engineering, Computer Science, Statistics.
• Advanced knowledge and 7+ years of experience in building and understanding of Anti-Money Laundering models and systems
• Strong familiarity with the industry practices in the field and knowledge of up-to-date Anti Money Laundering techniques
• CAMS certification (preferred)
• Fluency in Python, SAS and SQL
• Excellent written and oral communication skills with stakeholders of varying analytic skill and knowledge levels.
Skills:
Business Acumen
Critical Thinking
Regulatory Relations
Talent Development
Technical Documentation
Policies, Procedures, and Guidelines Management
Project Management
Risk Analytics
Risk Management
Stakeholder Management
Drives Engagement
Inclusive Leadership
Risk Modeling
Strategic Thinking
Written Communications
Shift:
1st shift (United States of America)Hours Per Week:
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