The role is as a Senior Quantitative Finance Analyst within the 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.

• Responsible for independently conducting quantitative analytics and complex modeling projects.

• Leads efforts in development of new models, analytic processes or system approaches.

• Creates documentation for all activities and may work with technology staff in design of any system to run models developed. Incumbents possess excellent quantitative/analytic skills and are able to influence strategic direction, as well as develop tactical plans.

• This role will support the AML Event Processor and respective team. The Event Processor is a consolidation engine that aggregates events from all detection channels and calculates aggregated risk scores for event groups based on individual risk factor scores.

Required Skills:

• Successful candidates will have a Masters or PhD in Math, Economics, Statistics, or similar discipline, and a minimum 5 years relevant experience.

• Ability to work in a large, complex organization, and influence various stakeholders and partners

• Self-starter; Initiates work independently, before being asked

• Strong team player able to seamlessly transition between contributing individually and collaborating on team projects; Understands that individual actions may require input from manager or peers; Knows when to include others

• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences

• Ability to effectively presents findings, data, and conclusions to influence senior leaders

• Strong programming skills, e.g. Python, SAS, MATLAB or similar language

• Strong analytical and problem-solving skills

Desired Skills:
The ideal candidate will possess the following skills and experience

• Solid understanding of AML and Global Financial Crime modelling techniques

• Experience with core GRA Model Development Tools (BitBucket, Horizon, PyCharm, JIRA, GRADOC)

• Broad experience in the design, implementation, and validation of risk models

• Good understanding of current US regulatory environment, including but not limited to AML

Shift:

Hours Per Week: