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AML Transaction Monitoring Analyst

Job

Google

Chicago, IL (In Person)

Full-Time

Posted 1 week ago (Updated 13 hours ago) • Actively hiring

Expires 7/6/2026

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Job Description

AML Transaction Monitoring Analyst corporate_fare Google place Chicago, IL, USA ; Austin, TX, USA bar_chart Early Early Experience completing work as directed, and collaborating with teammates; developing knowledge of relevant concepts and processes. info_outline
X Note:
By applying to this position you will have an opportunity to your preferred working location from the following: Chicago, IL, USA; Austin, TX, USA .
Minimum qualifications:
Bachelor's degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Mathematics, Information Systems) or equivalent practical experience. 1 year of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. 1 year of experience in an analytical, data science, or quantitative risk management role within AML compliance, trust and safety, or financial services.
Preferred qualifications:
Master's degree in a quantitative discipline. Experience writing and optimizing SQL queries to extract, clean, and analyze datasets. Experience building data visualizations or dashboards (e.g., Tableau, Looker, Business Intelligence Platform, or equivalent) and automating workflows (e.g., using Python, scripting, or basic automation tools). Excellent written and verbal communication skills. About the job Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about . Responsibilities Collaborate with the Transaction Monitoring Lead to develop, test, and deploy static rules and machine learning models that enhance AML detection. Maintain comprehensive documentation of monitoring logic, risk coverage, and tuning processes. Design AI agents and refine Large Language Model (LLM) prompts to accurately identify and classify financial crime patterns. Build visualization dashboards and automated workflows to report on performance and reduce manual tasks. Execute ad-hoc data queries and quantitative analysis to support technical projects and emerging risk scenarios.