The position is part of the Enterprise Risk Analytics (ERA) model development team for Anti-Money Laundering (AML) detection models. These models identify potentially suspicious behaviors for further evaluation by our in-house investigation teams. This area has a unique appetite for a wide scope of model methodologies, from simple rules-based models to advanced machine learning and AI models which facilitates opportunities for both immediate, effective contribution on team priorities and personal development through exposure to advanced modeling techniques. Our statistical toolkit includes various numerical procedures, with a recent emphasis on enhancing custom, AML domain-specific performance testing and evaluation capabilities. Python and PySpark serve as our primary programming languages, in addition to SQL for extracting data from Hadoop and other databases.

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.

As a Quantitative Finance Analyst within Enterprise Risk Analytics - AML model development team, the main responsibilities will include:

• Identifying and applying statistical techniques to support innovative, enhanced granularity of risk management capabilities

• Developing quantitative methods to support granular detection capabilities that meet risk management, line of business, and regulatory requirements

• Performing in-depth analysis on the Banks AML model suite and clearly articulating a holistic picture of model performance

• Communicating model performance to model stakeholders, including risk management, model development, model risk, and senior management with clear conclusions regarding accuracy and remediation areas as required

• Demonstrated ability to clearly articulate to senior stakeholders quantitative solutions that are designed to drive the business forward by addressing critical business problems"

Required Skills

• Graduate degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)

• 2+ years of experience in model development, statistical work, data analytics or quantitative research or PhD

• Strong Programming skills e.g. R, Python, SAS, SQL or other languages

• Strong analytical and problem-solving skills

Desired Skills

• Knowledge of predictive modeling, statistical sampling, optimization, machine learning and artificial intelligence techniques

• Strong technical writing, communication and presentation skills and ability to effectively communicate quantitative topics with non-technical audiences

• Experience with large data sets

• Effective at prioritization/time and project management

• Broad understanding of financial products

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