Associate – [BZ9279787]

Deutsche Bank•New York, NY

11d•Onsite

About The Position

Deutsche Bank USA Core Corporation seeks an Associate in New York, NY to enhance Deutsche Bank’s Bank-Secrecy-Act and Anti Money-Laundering (BSA/AML) capabilities by designing and supporting robust transaction monitoring technologies and controls to identify suspicious money laundering behavior and ensure data-driven alert generation for suspicious activity reporting.

Requirements

Master’s degree in Data Analytics or a related field or equivalent
One (1) year of experience developing and maintaining the Interim Compensating Control (ICC) framework in alignment with Federal Reserve Board (FRB) mandates
Experience leading support for internal audits and regulatory examinations conducted by major United States and international regulatory bodies
Experience modifying end-to-end data pipelines developed in Python and PySpark using Cloudera Data Science Workbench (CDSW)
Experience integrating enterprise job schedulers including Control-M to automate monthly batch-processing workflows
Experience executing full lifecycle tuning and optimization of United States Transaction Monitoring systems in alignment with Bank Secrecy Act and Anti-Money Laundering regulatory requirements
Experience applying statistical techniques including Interquartile Range (IQR) analysis, weighted average calculations, standard deviation thresholds, and historical transaction profiling to calibrate monitoring thresholds, reduce false positives, and enhance detection of potentially suspicious financial activity
Experience implementing end-to-end model validation through back-testing, behavioral segmentation, and statistical analysis using Python and PySpark
Experience testing pipelines on Cloudera Data Science Workbench (CDSW) and supporting deployment readiness using CyberArk for secure access, Control-M for workflow orchestration, and Bitbucket for codebase management and version control
Experience establishing strategy dashboards and visualizations in Microsoft Power BI, Tableau, and Matplotlib to compile multiple strategies and customer insights

Responsibilities

Designing and supporting robust transaction monitoring technologies and controls to identify suspicious money laundering behavior and ensure data-driven alert generation for suspicious activity reporting.
Developing and maintaining the Interim Compensating Control (ICC) framework in alignment with Federal Reserve Board (FRB) mandates.
Leading support for internal audits and regulatory examinations conducted by major United States and international regulatory bodies.
Modifying end-to-end data pipelines developed in Python and PySpark using Cloudera Data Science Workbench (CDSW).
Integrating enterprise job schedulers including Control-M to automate monthly batch-processing workflows.
Executing full lifecycle tuning and optimization of United States Transaction Monitoring systems in alignment with Bank Secrecy Act and Anti-Money Laundering regulatory requirements.
Applying statistical techniques including Interquartile Range (IQR) analysis, weighted average calculations, standard deviation thresholds, and historical transaction profiling to calibrate monitoring thresholds, reduce false positives, and enhance detection of potentially suspicious financial activity.
Implementing end-to-end model validation through back-testing, behavioral segmentation, and statistical analysis using Python and PySpark.
Testing pipelines on Cloudera Data Science Workbench (CDSW) and supporting deployment readiness using CyberArk for secure access, Control-M for workflow orchestration, and Bitbucket for codebase management and version control.
Establishing strategy dashboards and visualizations in Microsoft Power BI, Tableau, and Matplotlib to compile multiple strategies and customer insights.