JOB DESCRIPTION

Responsible for developing and maintaining quantitative/analytic models and applications in support of the firm’s risk management effort. This role focuses on the development of operations/data management policies, strategies, and operational guidelines for the organization’s various financial products as they relate to the analysis, tracking, and reporting of various risk metrics. This role often possesses an advanced degree in applied mathematics, statistics/probability, or other heavy quantitative disciplines. The Quantitative analytic teams are focused on and responsible for the development of the theory and mathematics behind various models. May report to either Quant Operations Exec or Quantitative Operations Manager

SKILLS:

• Experience in the development, validation, use, and auditing AML Models, including; AML Screening, economic sanctions, transaction monitoring, or fraud detection models, data visualization and data mining.
• Attention to Detail and awareness of AI / Machine learning concepts and ability to implement such strategies.
• Excellent analytic, technical, communication and auditing skills.
• Strong understanding of quantitative modelling concepts, financial instruments, and risk assessment methodologies.
• Good experience in Data Analytics and interpretation of large volumes of Data.
• Programming experience with any language like Python, Spark, R, SAS, SQL and related tools such as SQL Server, Toad, PyCharm, Jupiter Notebook, Hue, Beeline.
• Experience with MS Suite and any presentation and visualization tools.
• Experience with Horizon for project management and code control tools such GIT and bitbucket.

DESIRED SKILLS AND EXPERIENCE:

• Master’s or bachelor’s degree in finance, Economics, Mathematics, Statistics or related quantitative field. Advanced degrees in a quantitative field.
• Knowledge of Screening programs requirements
• Ability to work with teams spread globally, under pressure, meet deadlines and navigate change.
• Ability to work and interact with people from a diverse range of backgrounds and opinions.
• Experience in Global Banking & Markets business process is a plus
• Experience in screening applications like Fircosoft.
• Certified Anti-Money Laundering Specialist (CAMS)

• Conducting independent assessments on opportunities for use of models followed by the development and deployment of models. Included int his will be the continued building of analytical frameworks in order to test AML models for ongoing opportunities across functions in AML high risk detection operations. Including data and trend analysis as well as data modelling.
• Primary responsibility is to tune parameters or partner with model developers to re estimate model(s) to minimize the false negatives and identify triggers for false-positive Screening alerts to improve accuracy of model inputs, assumptions, methodologies, and model outcomes with business intelligence.
• Assess the model risk management framework of the organization, and controls related to model development, validation, implementation, and ongoing monitoring.
• Effectively manage the ongoing monitoring of the AML screening model by setting performance metrics, acceptable thresholds. Provide insights to the model owner and key stakeholders on the model performance. Engage with model risk management and LOB partners to identify causes when the metrics are in breach.
• Assist in on-boarding new applications / Clients into the Screening platform requiring detailed discussions, analytical thinking with various lines of businesses in understanding the nature and type of data received from and assist in data mapping into standard data layout acceptable for Sanctions screening.
• Manage the multiple on-going initiatives from various projects, understand the Screening needs from the cross-LOB projects, provide model or analytical requirements to the projects and track the status of the model development or any analytical support needed for the projects.
• Collaborate with cross-LOB teams to integrate data science solutions into existing AML systems including data management.
• Work with technology teams for requirements / testing and implementing changes to improve / automate processes and stay abreast of industry trends and emerging technologies including technical documentation.
• Communicate work through formal audit templates, reports, as well as through presentations to stakeholders and leaders. Work effectively as a team member with other quantitative analysts or data scientists within the organization or at the company.