AML Business Data Analyst
Jobgether · US
Extracted from the posting
Builds, validates, and tunes AML, sanctions screening, and fraud detection models for a bank or financial services firm. The role uses Python and SQL on large banking datasets with logistic regression, multinomial logit, XGBoost, LightGBM, and Random Forest. It includes reporting model results to senior management and regulators, with Git and GitHub for version control.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AML Business Data Analyst based in the United States.
The AML Business Data Analyst will apply advanced quantitative analysis and machine learning techniques to strengthen financial crime detection across banking and financial services. This role focuses on developing, validating, and optimizing analytical models for Anti-Money Laundering (AML), sanctions screening, and fraud prevention. You will work with large and complex banking datasets, using Python and SQL to identify patterns, improve data quality, and enhance model performance. The position combines statistical expertise, hands-on model development, and business understanding to support more accurate and effective risk detection. Working closely with technology, compliance, and model governance teams, you will translate analytical findings into practical recommendations. You will also communicate model performance and optimization outcomes to senior management and regulatory stakeholders.
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How Jobgether works:
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