Associate Director, FCC Change and Analytics - Newark, New Jersey, United States, 07175
We are a leading international bank focused on helping people and companies prosper across Asia, Africa and the Middle East.
To us, good performance is about much more than turning a profit. It's about showing how you embody our valued behaviours - do the right thing, better together and never settle - as well as our brand promise, Here for good.
We're committed to promoting equality in the workplace and creating an inclusive and flexible culture - one where everyone can realise their full potential and make a positive contribution to our organisation. This in turn helps us to provide better support to our broad client base.
The Role Responsibilities
Identify, design and test Detection Scenario (DS) models to improve quality of alerts generated using statistical modeling techniques. Propose new DS by identifying patterns using data mining techniques and advanced algorithms on customer data, transactional data and sanctions datasets. Develop dashboards and reports for the stakeholders to provide detailed analysis outcomes and presentations. Provide analytics input into Anti-Money Laundering components including Threshold Tuning and Alert Risk Scoring. Perform capacity planning for both short and long term based on volume analysis, dynamically forecast future volumes based on historical trends. Look for areas of opportunity in a bit to optimize operations. Maintain dashboards and metrics that allow the FCC to dynamically monitor operational metrics. Provide analytic insights into system optimization and to the Financial Crime Risk data governance Program.
Bachelor's degree or foreign equivalent in Mathematics, Statistics, Economics or a related quantitative field plus five (5) years experience in the job offered or a related position. Must have five (5) years of experience with all of the following: AML Surveillance & Sanction Screening in Financial Crime and Compliance domain for Correspondent Banking, Financial Market and Trade Payments systems; Operational, conceptual and architectural experience with Mantas, Norkom and Fircosoft systems; Experience in R, SQL, Base SAS & SAS Enterprise Miner, and Tableau for undertaking surveillance system optimization and developing Intelligence reports; Macros, V-Lookups, Pivots in Microsoft Excel; Application of Predictive Modelling and Risk and Data analytics in Financial Crime Compliance domain; AML Threshold Tuning, Customer segmentation and Alert Risk Scoring; Implementation of Data Quality management framework techniques such as Data profiling and Data lineage in Financial Crime Compliance domain; Univariate and Multivariate statistical methods used for AML threshold tuning such as Percentile analysis, Jump methodology, scenario Clustering and related techniques in threshold tuning. In the alternative the employer will accept three (3) years of university level study plus two (2) years of related work experience in lieu of a Bachelor's degree.
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