AML; Anti- Laundering Compliance Strategy Specialist - USDS

Position: AML (Anti-Money Laundering) Compliance Strategy Specialist - USDS
About the Team
USDS Financial Crimes Compliance is responsible for overseeing and operationalizing all aspects related to Anti-Money Laundering (AML) and sanctions compliance activities related to Tik Tok USDS. Collaborating cross-functionally with stakeholders across the U.S. and globally, we address complex and cutting-edge challenges, which include the identification of money-laundering, terrorist financing and sanction violations. We seek a highly motivated, experienced, and dynamic professional to join our team.

Responsibilities

* Lead the assessment, support, and optimization of data analytics and performance for our core financial crime systems. This involves close collaboration with data science and engineering teams to evaluate system features, data feeds, and usage, identifying implementation gaps, necessary controls, and ensuring alignment with our risk appetite.

* Validate new or updated technical controls during system changes, ensuring that automated features meet regulatory specifications and effectively replace or enhance existing manual controls before deployment.

* Manage and perform deep-dive investigations and exploratory data analysis to uncover emerging threats and anomalies, liaise with compliance, legal, and business teams to gather intelligence and ensure financial crime controls are aligned with organizational priorities.

* Document the methodology for customer, geography, and product risk which address money laundering, sanctions and other financial crime risks associated with our products along with the scoring process/rationale of risk and control.

* Translates complex business and regulatory objectives into detailed Business Requirements Documents (BRDs) and acts as the vital link between stakeholders and engineering teams.

* Review functional and technical specifications and success metrics to ensure technical roadmaps are precisely aligned with strategic goals and FCC standards.

* Maintain and enhance assigned FCC systems and controls, leveraging deep technical expertise to proactively anticipate issues, develop innovative improvements, and ensure robust system stability and efficiency.

* Drive all aspects of data and functional testing for AML and Sanctions monitoring systems including User Acceptance Testing (UAT) for new features/enhancements.

* Continuously monitor and rigorously assess the performance of AML and Sanctions systems using advanced data analytics tools, contributing critical insights to key Management Information (MI) reports.

* Develop and lead impactful analysis sessions for technology changes, validate the accuracy of operational procedures and controls, and spearhead the development of Compliance dashboards. Effectively present complex findings and strategic recommendations to diverse stakeholders.

* Perform special projects and additional duties and responsibilities as required.

Minimum Qualifications

* Bachelor's degree in Computer Science, Mathematics, Finance, or another quantitative field.

* 5+ years of hands-on experience supporting Anti-Money Laundering (AML) systems within financial crime compliance programs.

* Proven proficiency with data querying and analysis tools including Hive, SQL, Python, and business intelligence platforms like Tableau.

* Strong familiarity with financial crime industry practices and up-to-date knowledge of fraud and Anti-Money Laundering typologies.

* Excellent written and oral communication skills, with the ability to articulate complex technical concepts clearly to stakeholders with varying analytic skills and knowledge levels.

Preferred Qualifications

* Postgraduate degree (Master's or PhD) in Computer Science, Mathematics, Finance, or a related quantitative field along with 5+ years of progressive experience supporting and optimizing Anti-Money Laundering systems in a dynamic financial services or technology environment.

* Demonstrated experience in leading complex data mining, data scrubbing, and data analysis projects.

* Direct experience with major AML vendor platforms (e.g., Actimize, FICO, Oracle Mantas) and their specific configuration, scenario logic, and data models along with relevant Anti-Money Laundering certification, such as Certified Anti-Money Laundering Specialist (CAMS), or other globally recognized credentials focused on combating financial crime.

* Experience with new system implementations, including leading User Acceptance Testing (UAT), comprehensive data testing, impact assessments, and model validations.

* Familiarity with applying statistical modeling or machine learning techniques to enhance financial crime detection along with Proven ability to influence and drive consensus among cross-functional teams and leadership.