Anti-Money Laundering (AML) Quantitative Analyst

Position Description

As part of Morgan Stanley's ongoing commitment to prevent and detect money laundering and terrorist financing, the Firm has adopted a comprehensive, risk-based program to ensure compliance with counter-terrorism and anti-money laundering ("AML") laws, rules, regulations, and government guidance. The successful candidate will work closely with senior members of the AML Group and AML IT personnel in support of strategic projects and process improvements by analyzing "big data" using statistical packages.

Primary responsibilities will include:
• Evaluating existing surveillance models and scenarios; conducting model and scenario validation according to the Firm's and the regulators' standards of analytical rigor;
• Making recommendations to improve AML surveillance through the development of new risk models, model validation, statistical analysis of model thresholds, back testing, and other sensitivity and productivity analyses
• Supporting the AML Group's periodic risk assessments through the analysis of data elements related to potential indicators of customer, product, or geographic risk, evaluating and enhancing the AML Group's risk rating methodologies, and identifying new quantitative factors that can be incorporated into the risk assessment process;
• Assisting in the preparation of periodic and ad hoc AML and economic sanctions metrics reports for regulators, senior compliance management, the Global Compliance Committee and the Board Audit Committee, including through the evaluation and enhancement of existing metrics and supporting processes.

Additional responsibilities may be identified as the role evolves.*LI-KR

Skills Required

• Statistician that can apply data analysis and statistical modeling techniques to improve a business process and present recommendations in a non-technical, business-friendly way for consideration by senior management
• High level of computer literacy, including experience using statistical packages for research/modeling (e.g., SPSS, Matlab, SAS, etc.)
• Fluency with Excel required, including pivot tables and summary functions
• Self-sufficiency in SQL
• Experience with financial services data types (such as wires, checks, journals, and their data fields) and transactional risk management
• Proficiency with data warehousing designs, data architecture and database technologies
• Strong business analysis and project management skills

Skills Desired

• Familiarity with surveillance model design strongly preferred

October 14, 2013 • Tags: , • Posted in: Financial

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