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BACKGROUND:
Global Financial Crimes Automated Detection & Monitoring team seeks a Quantitative Scenario Analyst – Anti-Money Laundering (AML) to conduct independent testing and review of complex models used to monitor and mitigate money laundering risk. These scenarios identify potentially suspicious behaviors for further evaluation by our in-house investigation teams. 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 overseeing statistical and machine learning models to manage the bank’s AML models and model systems.
The Role will interact with a wide variety of stakeholders including Financial Crimes Investigations, business risk managers, model developers, model risk management, model implementation, and technology teams. The qualified candidate will be responsible for overseeing a broad range of model risk oversight activities, including:
• Performing in-depth analysis on the Bank’s AML model suite and clearly articulating a holistic picture of model performance, monitoring and targeted assessments.This role is also responsible for defining the vision and roadmap for a product or technology solution, defining and prioritizing deliverables in the product book of work, and articulating this to both business stakeholders and technology development teams. The Sr. Product Owner/Sr. Business Analyst is experienced in the role of a Product Owner, expert of the product, and have a deep understanding of the business and/or technology domain, while also having advance quantitative/analytic skills to influence the Financial Crimes program strategic transaction monitoring and data management direction.
Skills:
Qualifications:
• Bachelor's Degree (or Higher) in a quantitative field such as Mathematics, Computer Science, Statistics or 5+ years of experience in oversight and understanding of Anti-Money Laundering models and systems
• Fluency in Python, SAS and SQL
• Strong familiarity with the industry practices in the field and knowledge of up-to-date Anti Money Laundering techniques
• Proficiency in Microsoft Excel / data analytics; ability to analyze and manipulate large data sets
• Flexible to perform other functions as requested by management
• CAMS certification (preferred)
Shift:
1st shift (United States of America)Hours Per Week:
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