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.
Overview of the Role
As a Senior Quantitative Finance Analyst on the Enterprise Risk Analytics team, your main responsibilities will involve:
• Applying quantitative methods to develop capabilities that meet line of business, risk management and regulatory requirements
• Maintaining and continuously enhancing capabilities over time to respond to the changing nature of portfolios, economic conditions and emerging risks
• Understanding and executing activities that form the end-to-end model development and use life cycle
• Clearly documenting and effectively communicating quantitative methods as part of ongoing engagement with key stakeholders, including the lines of business, risk managers, model validation, technology 

Position Overview
 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."

Required Education, Skills, and Experience
• Graduate degree in quantitative discipline (e.g. Mathematics, Economics, Engineering, Finance, Physics)
• 5 years professional 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
• Strong communication skills and ability to effectively communicate quantitative topics to technical and non-technical audiences
• Ability to work in a highly controlled and audited environment
• Effective at prioritization, and time and project management
• Sees the broader picture and is able to identify new methods for doing things
• Strategic thinker that can understand complex business challenges and potential solutions
Desired Skills and Experience
 • Experience using data mining and other advanced analytical techniques to aggregate data for model development and/or to produce management reporting
• Experience designing, developing, and applying scalable Machine Learning and Artificial Intelligence solutions
• Experience with data analytics and visualisation tools (e.g., Alteryx, Tableau, MicroStrategy)
• Experience with LaTeX
• Demonstrated ability to drive action and sustain momentum to achieve results
• Identifies, assigns, and manages project tasks and timelines across teams
• Experience with engineering complex, multifaceted processes that span across teams; Able to document process steps, inputs, outputs, requirements, identify gaps and improve workflow.